Data Sources SQL Jobs in Bengaluru

Position: Mechatronics & Big Data Scientist Developer Department: Research & Development Reporting To: General Manager Location: Bengaluru Key Responsibilities Machine Learning: Select features, build, and optimize classifiers using advanced machine learning techniques. Data Mining: Perform data mining using state-of-the-art methods to extract valuable insights from large datasets. Data Enhancement: Extend the company s datasets with third-party data sources when necessary to improve model accuracy and relevance. Data Collection & Processing: Improve data collection procedures to include all necessary information for building analytic systems. Data Cleansing & Integrity: Process, cleanse, and verify the integrity of data used for analysis to ensure reliable results. Ad-hoc Analysis: Perform ad-hoc analysis as needed, presenting the results in a clear, actionable manner. Anomaly Detection: Design and implement automated anomaly detection systems, tracking their performance over time to ensure accuracy. Behavioral Competencies Data-Driven: Strong inclination toward working with data and applying analytical thinking to solve complex problems. Detail-Oriented: Meticulous in data analysis and system development to ensure quality and precision in results. Skills and Expertise Machine Learning Algorithms Strong understanding of machine learning techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Data Science Tools Experience with common data science toolkits like R, Weka, NumPy, and MatLab. Proficiency in at least one (preferably NumPy or R) is highly desirable. Data Visualization Skilled in data visualization tools such as D3.js, GGplot, or similar. Database Management Experience with query languages such as SQL, Hive, Pig, NiFi, or others depending on the company s stack. Familiarity with NoSQL databases like InfluxDB, MongoDB, Cassandra, HBase. Statistical Analysis Strong applied statistics skills, including distributions, statistical testing, and regression analysis. Programming Skills Good scripting and programming skills in languages like PHP, Slim, SQL, and Laravel. Big Data Technologies Knowledge of Hadoop, HDFS, NiFi, and other big data platforms and technologies. Qualifications Essential: MTech, MS, or equivalent in Mechatronics, Computer Science, or a related field. Experience: Minimum 2 years of hands-on experience in developing SDKs and working with Big Data platforms. Proven track record in machine learning, data mining, and data science projects. Qualification : MTech, MS, or equivalent in Mechatronics, Computer Science, or a related field

Analytics Engineer Location: Bengaluru Work Type: Full-Time About Postman Postman is the world s leading API platform, used by over 40 million developers and 500,000 organizations, including 98% of the Fortune 500. Our mission is to build an API-first world, simplifying every step of the API lifecycle and enabling teams to create better APIs, faster. Founded in Bengaluru, Postman is headquartered in San Francisco, with offices in Boston, New York, and Bengaluru. We are privately held, backed by Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. The Opportunity We are seeking an Analytics Engineer to join our Data Team and help strengthen the foundation of our modern data stack. In this role, you will own critical transformation pipelines, design scalable data models, and ensure that our analytics environment is performant, reliable, and future-ready. You will operate with a high degree of independence, driving projects from design through production, while implementing best practices in dbt, semantic layers, medallion architecture, and lakehouse paradigms. Key Responsibilities Take ownership of large portions of our dbt project (3k+ models), ensuring scalability, maintainability, and adherence to best practices. Design and implement robust data models, including dimensional modeling, incremental strategies, and Slowly Changing Dimensions (SCDs). Establish and enforce dbt test coverage, automated quality checks, and CI/CD pipeline standards using GitHub Actions. Profile and optimize SQL queries and warehouse performance for efficiency and cost reduction. Build and refine our semantic layer, ensuring consistent business logic across Looker, Redash, and downstream tools. Collaborate with analysts and business partners to define metrics and deliver self-serve data assets. Document models, lineage, and transformation logic to make data discoverable and usable across the company. Contribute to shaping team standards and playbooks, collaborating with analysts on modeling and transformation best practices. Stay ahead of modern data stack innovations, including dbt metrics layer, universal semantic layers, data contracts, and observability. Enabling Self-Serve Analytics & AI Build transformations that empower business stakeholders and analysts to explore data confidently. Ensure metric definitions are consistent, discoverable, and reusable across BI tools. Prepare clean, structured, and accessible datasets for AI-driven initiatives like conversational analytics and anomaly detection. Partner with Data Science & ML teams to provide reliable pipelines that accelerate experimentation and AI/ML deployment. About You 3 5 years of experience in analytics engineering roles. Advanced SQL skills (query optimization, performance tuning). Strong proficiency in dbt Core: models, macros, snapshots, sources, and custom materializations. Solid background in data modeling techniques (Kimball, SCD handling, incremental pipelines). Practical experience with semantic layers and BI integration (LookML, dbt metrics, or equivalent). Familiarity with Medallion architecture and modern lakehouse approaches. Hands-on experience with Redshift; exposure to Databricks is a plus. Proficiency with GitHub and CI/CD pipelines for analytics code. Strong fundamentals in data quality, governance, and lineage tracking. Flexible schedule with a hybrid work model. Full medical coverage, flexible PTO, wellness reimbursement, and monthly lunch stipend. Access to wellness programs, team-building events, and donation-matching initiatives. An inclusive, collaborative culture where everyone can thrive and grow. Our Values Curiosity: Explore and innovate fearlessly. Transparency: Communicate openly about successes and failures. Focus: Set clear goals aligned with a bold vision. Inclusion: Every voice matters. Excellence: Deliver the best products and experiences together.

Position: Data Analyst 3 Location: Bengaluru Department: Growth & Strategy Employment Type: Full-Time Job Description: We are seeking an experienced Data Analyst to develop and maintain interactive dashboards, design data models, and extract actionable insights to support strategic business decisions. This role requires proficiency in Tableau and/or Qlik Sense and the ability to lead a team of analysts. Key Responsibilities: Develop, maintain, and enhance interactive dashboards and reports using Tableau and/or Qlik Sense. Design and implement efficient data models to underpin visualizations and analytical processes. Analyze data from multiple sources to identify trends, patterns, and actionable insights. Write scripts and utilize calculated fields to transform and manipulate data within visualization platforms. Migrate dashboards between platforms (e.g., Qlik Sense to Tableau) as needed. Adhere to best practices in data visualization, dashboard design, and data modeling. Communicate findings effectively to stakeholders and collaborate with cross-functional teams such as sales, marketing, and engineering. Mentor and lead a team of data analysts, fostering growth and knowledge sharing. Required Skills and Experience: Minimum 4 years of relevant experience in data analysis and visualization. Proficiency in Tableau and/or Qlik Sense, including scripting and calculated fields. Strong data modeling skills and experience with relational databases (e.g., SQL Server, Oracle). Excellent analytical and problem-solving abilities. Outstanding communication and presentation skills. Industry experience in Fintech, Payments, Finance, Banking, Digital Commerce, Healthcare, or related sectors is a plus. Who You Are: A problem-solver with a knack for uncovering insights from complex data sets. An excellent communicator, able to explain data-driven insights clearly and effectively. Hands-on and proactive, committed to staying updated with the latest tools and technologies. A respected team player and leader known for your analytical depth and influence.

Position: Data Science Specialist Employment Type: Full-time Location: Bangalore, On-site Experience Required: 1 to 6 years (Mindset > Experience) About the Role: We re seeking a mission-driven, hands-on Data Analytics Specialist passionate about impact. This is not a typical analytics role you will drive key business metrics across clinical operations, stakeholder reporting, and automation. Collaborate closely with leadership, radiologists, operations, product teams, and AI engineers to ensure every decision is data-driven, actionable, and scalable. If you thrive on building dashboards, automating processes, streamlining pipelines, and driving growth through insights, this is your playground. Key Responsibilities: Own Business KPIs: Take full ownership of company-wide metrics, ensuring their accuracy, relevance, and actionability through stakeholder alignment. Data Engineering: Build and optimize ETL/ELT pipelines integrating data from Postgres, ClickHouse, and other sources. Dashboards & Reporting: Design and maintain intuitive dashboards (Metabase, Power BI, Tableau, Google Data Studio) that stakeholders actively use. Backend Data Transformation: Write clean, reusable code to convert raw data into actionable insights. API Development: Build and maintain internal APIs to serve analytics data to frontend and production systems. Email Automation: Develop real-time and scheduled email reports delivering dynamic insights to stakeholders. Spreadsheet Expertise: Automate and manipulate complex data in Excel/Google Sheets for detailed analysis and reporting. AI & Automation: Collaborate with AI teams to integrate predictive algorithms and automate analytics workflows. Business Acumen: Develop deep understanding of the teleradiology ecosystem clinical workflows, operations, financials, and tech platforms. Proactive Collaboration: Identify data gaps, flag inconsistencies, recommend improvements, and work closely with leadership. Required Skills: Strong Python skills for data analytics (Pandas, NumPy, FastAPI, Jupyter, etc.) Proficient in SQL (ClickHouse, PostgreSQL) with experience optimizing queries End-to-end dashboard ownership from data modeling to UI presentation Experience building or integrating APIs for analytics Advanced spreadsheet skills and formula-driven reporting Experience working with AI/ML models in applied settings (preferred) Hands-on backend data transformations, version control, and automation Familiarity with full-stack development frameworks (bonus) Bonus / Nice to Have: Exposure to dbt, Airflow, ChromaDB, Streamlit, Plotly Knowledge of data privacy, compliance, and healthcare analytics Experience building analytics platforms for SaaS or health-tech companies Mindset We re Looking For: 10x Hustler: Ready to learn fast and go the extra mile to solve problems. Obsessed with Accuracy: Data must be flawless before release. Extreme Ownership: Proactive in driving results without waiting for instructions. Fast Learner: Able to pick up new tools and concepts quickly. Business First, Code Later: Focused on impact, not just coding. Be part of India s fastest-growing teleradiology platform Direct access to leadership and real-world business impact Build game-changing analytics systems and influence strategy Gain exposure to AI, automation, product, and operations in one role Clear ramp-up roadmap and growth plan Expectations in First 3 Months: Build an end-to-end dashboard from scratch Clean up at least one messy data pipeline Automate a stakeholder email update Validate accuracy across critical business metrics Understand full-stack platform structure and propose an improvement

Senior Associate Data Engineering L2 Location: Bengaluru, India Department: Engineering Data Employment Type: Full-Time About the Role As a Senior Associate Data Engineering (L2) at Publicis Sapient, you will lead technical solutions that drive digital transformation by building scalable, high-performance data platforms. You ll be responsible for translating business and technical requirements into modern, data-centric solutions using Big Data technologies, cloud services (Azure), and advanced data engineering practices. Key Responsibilities Design and implement data ingestion, integration, and transformation processes from multiple heterogeneous sources in both batch and real-time. Build scalable data platforms using Hadoop stack components such as HDFS, Kafka, Spark, Hive, NiFi, Oozie, Airflow, Flink, and Storm. Develop real-time analytics, aggregation, and search features to support various data-driven applications. Collaborate closely with cross-functional teams on data infrastructure, computation frameworks, and data visualization. Apply cloud-native principles and Azure services to build and deploy data pipelines. Ensure performance optimization and data pipeline tuning. Work with NoSQL and MPP platforms like MongoDB, Cassandra, Redshift, Azure SQL DW, HBase, BigQuery. Contribute to infrastructure, automation, and DevOps for data pipelines using CI/CD practices. Ensure data governance, lineage, and cataloging using tools like Collibra or Alation. Required Qualifications 6 8 years of professional experience in software/data engineering. Minimum of 3 years hands-on experience with Big Data technologies. Strong programming expertise in Java (preferred), Scala, or Python. Expertise in the Hadoop ecosystem and real-time stream processing tools (Kafka, Pulsar, Spark Streaming, etc.). Hands-on experience with Azure data services (e.g., Data Factory, Synapse, ADLS, Databricks). Experience working with modern ETL tools (Informatica, Talend, etc.) and traditional RDBMS platforms (Oracle, PostgreSQL, SQL Server, MySQL). Bachelor's degree in Computer Science, Engineering, or related field. Nice to Have Certifications in Azure Data Engineer, GCP Big Data, or related cloud specializations. Experience with distributed messaging frameworks (ActiveMQ, RabbitMQ, Solace). Familiarity with microservices architecture and search technologies (Elasticsearch). Performance tuning of distributed data processing systems. Exposure to data governance, security, and metadata management. Benefits and Culture at Publicis Sapient Gender-neutral workplace policies 18 paid holidays annually Generous parental leave + new parent transition support Flexible work arrangements Access to Employee Assistance Programs (wellness & well-being) A dynamic culture focused on learning, creativity, and collaboration Qualification : Bachelor's degree in Computer Science, Engineering, or related field.

Position: Business Technology Data Engineer Location: Bengaluru, India (Hybrid 3 days onsite) Company: Samsara Technologies India Pvt. Ltd. About Samsara Samsara (NYSE: IOT) is a leader in the Connected Operations Cloud, enabling businesses across industries like transportation, logistics, manufacturing, and field services to harness IoT data for safety, efficiency, and sustainability improvements. Samsara helps organizations digitize physical operations at scale, improving outcomes that impact global infrastructure. Role Overview Samsara is seeking a Business Technology Data Engineer to join its Data & Analytics team within the Business Technology division. In this role, you will design, build, and optimize end-to-end data pipelines and infrastructure for various business-critical systems across CRM, marketing, support, and product platforms. You'll collaborate with teams across the company to build reliable and scalable data solutions that power reporting, automation, and analytics. This hybrid role requires working 3 days per week from the Bengaluru office and 2 days remotely, with working hours aligned to India Standard Time (IST). Key Responsibilities Data Engineering & Platform Development Design and maintain ETL/ELT pipelines that integrate and transform data across business systems. Build scalable data infrastructure to support advanced analytics and real-time reporting needs. Write Python and SQL scripts for data ingestion, transformation, and validation. Data Integration & Enablement Work with diverse data sources: CRM, product telemetry, marketing automation, support ticketing, and order flow systems. Develop and support data lake and data warehouse solutions using Snowflake, Redshift, Databricks, or BigQuery. Ensure interoperability between applications and data layers. Performance & Quality Monitor and optimize pipeline performance, implement observability and alerting. Improve data quality, lineage, and governance across systems. Partner with internal stakeholders (e.g., Sales Ops, Marketing Ops, Analytics) to deliver reliable data products. Minimum Qualifications Bachelor s degree in Computer Science, Data Engineering, or related field. 5+ years of professional experience in data engineering. 3+ years experience building and maintaining end-to-end pipelines in a modern data stack. Strong in SQL and Python. Hands-on experience with: ETL tools: Fivetran, dbt Cloud: AWS (preferred), GCP, or Azure Databases: MySQL, PostgreSQL, Oracle, or similar Data Warehouses: Snowflake, Redshift, BigQuery, Databricks Preferred Qualifications Familiarity with API-based ingestion, serverless architecture (Lambda, API Gateway, SQS, etc.). Experience with monitoring tools (DataDog, CloudWatch, Splunk). Comfortable engaging stakeholders to translate business needs into data solutions. Proficiency in Docker, Kubernetes, or AWS Fargate is a plus. Qualification : Bachelors degree in Computer Science, Data Engineering, or related field

Position Title: Senior Data Engineer Databricks, PySpark, Cloud Platforms Location: Bengaluru Bellandur (GTP) Employment Type: Full-time Job Summary Synechron is looking for a Senior Data Engineer to join our advanced analytics team in Bengaluru. In this role, you will architect and build scalable, high-performance data pipelines that power data science, analytics, and business intelligence initiatives. You ll work with modern tools including Databricks, PySpark, and cloud data platforms, while collaborating across teams to ensure high-quality, secure, and efficient data solutions. Key Responsibilities Design, develop, and maintain large-scale, secure, and efficient data pipelines using Databricks, PySpark, and cloud-native tools. Partner with data scientists, analysts, and business stakeholders to translate requirements into robust data solutions. Integrate data from various structured, semi-structured, and streaming sources. Ensure high standards for data quality, performance optimization, security, and cost efficiency. Drive data pipeline automation, orchestration, and monitoring using tools like Airflow. Lead troubleshooting efforts, performance tuning, and enhancements of existing pipelines. Stay informed about emerging data technologies and recommend adoption where relevant. Technical Skills Core Expertise Programming: Python (expert), SQL (advanced), PySpark. Platforms: Databricks (clusters, notebooks, workflows), AWS/Azure/GCP. Data Orchestration: Apache Airflow (or similar). Data Warehousing: Snowflake (preferred), data modeling, ETL/ELT pipelines. Streaming: Kafka or other stream processing tools. DevOps: CI/CD (GitLab CI, Jenkins), version control (Git), containerization (Docker/Kubernetes preferred). Security: Familiarity with encryption, access controls, and compliance best practices. Experience 8+ years of experience in data engineering or related roles. Proven expertise in developing and deploying scalable data pipelines using Databricks, PySpark, and SQL. Hands-on experience with cloud platforms (AWS, Azure, or GCP). Strong background in data warehousing, especially with Snowflake. Exposure to real-time data processing and orchestration tools. Experience implementing CI/CD pipelines for data workflows is a plus. Daily Responsibilities Build and optimize data ingestion, transformation, and storage workflows. Collaborate with cross-functional teams to align data solutions with business objectives. Monitor, troubleshoot, and continuously improve pipeline performance. Conduct data quality checks, ensure governance and compliance standards. Contribute to technical documentation, code reviews, and team knowledge sharing. Qualifications Bachelor s or Master s degree in Computer Science, IT, or related field. Relevant certifications (e.g., Databricks Certified Data Engineer, AWS Certified Data Analytics) are preferred. Professional Competencies Strong problem-solving and analytical mindset. Effective communicator with ability to collaborate across technical and non-technical teams. Time management and prioritization skills under tight deadlines. Proactive leadership and a passion for innovation. Commitment to ethical data use and data security. Diversity & Inclusion at Synechron Synechron is committed to building an inclusive, diverse, and equitable workplace. Through our global Same Difference DEI initiative, we celebrate and support people from all backgrounds, including race, gender, sexual orientation, religion, age, disability, and more. We offer flexible work arrangements, continuous learning, internal mobility, and mentoring programs to support every employee s growth. Qualification : Bachelors or Masters degree in Computer Science, IT, or related field

Data Engineer Location: Bengaluru Department: Global Strategic Services Data Engineering EMEA Type: Full-Time | Hybrid About Cognite Cognite is a global SaaS company at the forefront of industrial digital transformation. Our core platforms Cognite Data Fusion (CDF) and Cognite Atlas AI leverage AI and data to solve complex challenges across oil & gas, chemicals, pharma, manufacturing, and energy sectors. Recognized globally for innovation, Cognite helps businesses improve efficiency, reduce costs, and operate more sustainably. Our Values Impact: We focus on outcomes that truly make a difference. Ownership: We take responsibility and work inclusively to deliver success. Relentless: We are persistent problem-solvers who view challenges as growth opportunities. About the Team You ll join Cognite s Global Customer Success (GCS) organization spanning offices in Oslo, Austin, Houston, Tokyo, and now Bengaluru. The GCS team includes Project Managers, Data Engineers, Data Scientists, and Solution Architects, all working on high-impact industrial use cases across regions including MENA and SEA. About the Role As a Data Engineer, you'll play a key role in solving real-world industrial problems by designing, building, and optimizing scalable data architectures. You ll create robust pipelines to integrate and contextualize data using Cognite Data Fusion, working closely with cross-functional teams. This is also a growth role with the opportunity to step into a Tech Lead position. Key Responsibilities Design and implement scalable data solutions using Cognite Data Fusion. Integrate data sources using Cognite connectors, SQL, Python/Java, and REST APIs. Develop custom data models for cleansing, discovery, and mapping. Work with data scientists, architects, and PMs to deliver client outcomes. Conduct code reviews and apply best practices in maintainability and quality. Support customers and partners with data engineering tasks and challenges. Collaborate with Engineering and Product teams to influence product roadmap. What You ll Bring Bachelor's or Master s in Computer Science or related field. 3 5 years of experience in data-focused, customer-facing roles. Strong experience with Python, SQL, and REST APIs for production-grade pipelines. Familiarity with data from industrial domains like oil & gas or manufacturing is a plus. Experience with Kubernetes, Azure/GCP, and modern DevOps practices. Comfortable with Git, CI/CD, and cloud-native deployment workflows. A proactive, collaborative mindset with a passion for problem-solving and learning. Join a diverse global team with 70+ nationalities and a strong commitment to DEI. Work in a modern hybrid environment at our Bengaluru office (Rathi Legacy, Hoodi). Be part of a flat, transparent culture with direct access to leadership. Build cutting-edge solutions and influence how industries evolve digitally. Learn from top engineers and contribute to ambitious, high-impact projects. Enjoy a respectful, fun, and collaborative workplace where your voice matters. If you re excited to build data infrastructure that powers real change in heavy industries, Cognite offers you a platform to grow, lead, and innovate. We welcome candidates from all backgrounds and identities apply today and be part of something meaningful. Qualification : Bachelor's or Masters in Computer Science or related field.

Senior Data Analyst Location: Bangalore, India Office About the Team Rubrik s Legal Team plays a crucial role in securing the world s data by providing legal expertise across contracts, intellectual property, privacy, employment law, trade compliance, and litigation. The team fosters a culture of innovation, ownership, and collaboration as we build an iconic company. About the Role Rubrik s Legal Operations Team is looking for a skilled and motivated Senior Data Analyst to drive data-driven decision-making and operational efficiency. You will work closely with the Legal department to analyze, visualize, and report legal and compliance data, enabling strategic insights and process improvements. This role requires technical expertise and the ability to translate complex data into actionable business intelligence. Key Responsibilities Collect, analyze, and interpret legal and compliance data from various sources. Develop and maintain dashboards and reports using tools like Snowflake, Tableau, Smartsheets, PowerPoint, and Google Sheets. Track compliance initiatives and identify trends, risks, and improvement opportunities. Collaborate with Legal teams to define KPIs and metrics. Present data insights clearly to stakeholders to guide strategic decisions. Ensure data quality, integrity, and regulatory compliance. Support process optimization initiatives within Legal Operations. Manage reconciliation, validation, and data integrity tasks for critical legal projects. Create executive-level presentations demonstrating data trends and business impacts. Experience and Skills Required 5-8 years of experience in data analytics, preferably supporting legal, compliance, or operations teams. Proficiency in SQL, Tableau, Smartsheets, Excel, PowerPoint, and GSuite. Experience with case management systems and compliance datasets is a plus. Bachelor s degree in Data Science, Business Analytics, Computer Science, Finance, or a related field. Strong analytical skills with the ability to interpret large datasets and provide actionable insights. Excellent written and verbal communication skills, with experience presenting to cross-functional teams and executives. Familiarity with legal and compliance standards preferred but not mandatory. Detail-oriented with strong project ownership and process improvement mindset. Join Us in Securing the World's Data Rubrik (NYSE: RBRK) is on a mission to secure the world s data. Our Zero Trust Data Security platform leverages machine learning to safeguard data across enterprise, cloud, and SaaS applications helping businesses stay resilient against cyberattacks and operational disruptions. Qualification : Bachelors degree in Data Science, Business Analytics, Computer Science, Finance, or a related field.

Data Engineer, Product Analytics Location: Bangalore, India Full Time Company: Meta Meta is looking for an experienced Data Engineer to join our Product Analytics team. In this role, you will work on some of the most extensive data sets in the world, crafting experiences for billions of people and millions of businesses. Your technical expertise and analytical mindset will help shape data solutions across Meta to drive user experience optimization, growth, and strategy. You'll work alongside software engineers, data scientists, and product managers to tackle the most interesting data challenges at a scale few companies can match. Key Responsibilities: Conceptualize and own the data architecture for multiple large-scale projects, balancing design and operational cost-benefit tradeoffs. Design and contribute to frameworks that improve logging data efficacy, working with data infrastructure teams to resolve issues. Collaborate with engineers, product managers, and data scientists to understand data needs and represent insights meaningfully. Define and manage Service Level Agreements (SLAs) for all data sets in allocated areas of ownership. Implement and maintain security models based on privacy requirements and ensure safeguards are followed to ensure data quality. Design, build, and launch sophisticated data models and visualizations that support multiple use cases across various products. Address complex data integration challenges using optimal ETL patterns, frameworks, and techniques from structured and unstructured data sources. Optimize existing processes, pipelines, dashboards, and systems to enhance the development of data artifacts. Influence product and cross-functional teams to identify data opportunities that will drive impact. Mentor junior team members by providing constructive feedback and receiving feedback to grow as a team. Minimum Qualifications: Bachelor s degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience. 4+ years of experience in roles focused on data engineering, data analysis, or similar positions, working with SQL, ETL, data modeling, and programming languages (e.g., Python, C++, Scala). Experience with SQL, ETL processes, and data modeling, along with at least one programming language (e.g., Python, C++, C#, Scala). Preferred Qualifications: Master's or Ph.D. degree in a STEM field (Science, Technology, Engineering, Mathematics). About Meta: Meta builds technologies that help people connect, find communities, and grow businesses. Since launching Facebook in 2004, we have revolutionized how people connect. Our apps, including Messenger, Instagram, and WhatsApp, empower billions worldwide. Now, Meta is moving beyond 2D screens towards immersive experiences like augmented and virtual reality, building the next evolution in social technology. When you join Meta, you help shape the future of digital connection, taking us beyond screens, distance, and even the rules of physics. Equal Employment Opportunity: Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based on race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Qualification : Bachelors degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.

Data Engineer (Python/Dataiku/Spark/SAS DI) Location: Bangalore Type of Employment: Full-Time Experience Required: 3 to 5 years Job Overview: We are looking for a passionate Data Engineer with expertise in Python, Dataiku, Spark, or SAS DI to join our dynamic team. In this role, you will collaborate with clients to build data pipelines that support their Data and Analytics journey. As a member of our team, you will be responsible for driving data engineering initiatives, developing and implementing ETL solutions, and optimizing data workflows for efficiency and scalability. Key Responsibilities: Data Engineering Initiatives: Collaborate with clients to define and implement data engineering initiatives based on business needs. ETL Development: Design and develop data integration solutions using tools like Python, Dataiku, Spark, and SAS DI. Develop and maintain automated data pipelines for real-time and batch data ingestions. Performance Tuning: Conduct performance tuning and optimize queries and data models to enhance performance and scalability. Database Design: Design and implement database objects such as tables, views, schemas, and stored procedures. Ensure data quality and consistency across the data warehouse. Collaboration: Work closely with cross-functional teams to translate business requirements into technical solutions and communicate effectively with clients across multiple regions. Troubleshooting: Troubleshoot and resolve data-related issues while ensuring the quality and integrity of the data. Project & Technical Leadership: Act as the technical lead or single point of contact (SPOC) for the client and internal teams, ensuring smooth project delivery. Essential Skills: Data Engineering Tools: Experience with Python, Dataiku, Spark, and SAS DI. SQL Proficiency: Strong SQL experience for extracting data from various databases and performing data analysis. ETL Development: Expertise in designing and developing ETL processes to integrate data from diverse sources into a data mart layer. Data Modeling: Understanding of data modeling concepts, including relational and dimensional modeling. BI Knowledge: Basic understanding of Business Intelligence (BI) tools and analytics needs. Communication Skills: Excellent communication skills to understand business requirements and translate them into technical solutions. Desirable Skills: Data Analysis: Strong analytical skills to perform data analysis, especially for banking products data. BI Tools: Experience with MicroStrategy or Power BI for reporting and dashboarding. Qualifications: 3+ years of experience designing and developing scalable data integration solutions. Familiarity with data analytics and reporting needs. Technical certifications that align with your continuous learning aspirations. Qualities: Strong problem-solving skills with a systematic approach to resolving issues. Ability to influence and implement change confidently. Excellent team player who works effectively in cross-functional teams. Strong communication and presentation skills, capable of interacting with clients and presenting ideas persuasively. Fluent in English, both written and spoken, for effective communication. Opportunity to work with cutting-edge data engineering tools and technologies. Be a key player in building and optimizing data pipelines for clients data and analytics needs. Competitive salary, benefits, and a dynamic, innovative work culture.

Azure Data Engineer IBM Consulting Client Innovation Center Location: Bengaluru, India Experience: 7+ Years (Minimum 4+ Years in Azure Technologies) Job Type: Full-Time Education Required: Bachelor s Degree (Master s preferred) Introduction: Join IBM Consulting at our Client Innovation Center in Bengaluru, where we deliver deep technical and industry expertise to a wide range of public and private sector clients. Our delivery centers focus on innovation, agility, and adoption of next-gen technologies to transform businesses locally and globally. Your Role & Responsibilities: Design and develop scalable data engineering solutions on Microsoft Azure. Build, optimize, and manage data pipelines and ETL workflows using tools like Azure Data Factory, ADLS, and Databricks. Write clean, efficient code using PySpark, PL/SQL, and Spark SQL. Integrate and manage data from various sources, both structured and unstructured. Work with SQL, Postgres, Cassandra, and Cosmos DB. Utilize Azure services such as Stream Analytics, SQL DW, Azure Functions, ARM Templates, and Analysis Services. Implement and maintain serverless architectures for modern data solutions. Ensure high-quality data delivery, security, and compliance across systems. Collaborate across teams and contribute to solution design, code reviews, and documentation. Required Skills & Experience: Bachelor s degree in Computer Science, Information Systems, or related technical field. 7+ years total experience in Data Engineering, with 4+ years in Azure-based data projects. Strong hands-on experience with: Azure Data Factory, Data Lake (ADLS), Databricks Programming: Python, PySpark, PL/SQL, Spark SQL Databases: SQL, Postgres, Cassandra, Cosmos DB Solid grasp of data warehousing, relational databases, and cloud-based architectures. Familiarity with version control tools like Git and CI/CD pipelines. Preferred Skills & Qualifications: Master s Degree in a relevant field. Experience with: ARM Templates, Azure Functions, Serverless Architectures Object-oriented scripting languages (Python, Scala, etc.) Excellent problem-solving and communication skills. Ability to work in a fast-paced environment and collaborate effectively with teams and stakeholders. What You ll Get: Work on high-impact, global projects with cutting-edge Azure technologies. Be part of a collaborative and forward-thinking IBM team. Opportunities for professional growth, upskilling, and certifications. A dynamic work culture focused on innovation, agility, and client success. Join us in Bengaluru and be part of IBM s journey in shaping the future of data engineering. Qualification : Bachelors degree in Computer Science, Information Systems, or related technical field.

Job Title: Data Scientist Location: Bengaluru Experience: 4+ Years About Linarc: Linarc is revolutionizing the construction industry. As the emerging leader in construction technology, we are redefining how projects are planned, executed, and delivered. Built for general contractors, construction managers, and trade partners, Linarc offers a next-generation platform that delivers unmatched collaboration, automation, and real-time intelligence to construction projects. Our mission is to eliminate inefficiencies, streamline workflows, and drive profitability, empowering teams to deliver projects faster, smarter, and with greater control. Join us in shaping the future of construction tech. If you thrive in a dynamic, fast-growing environment and want to make a significant impact, Linarc is the place for you. This is a full-time position based in Bengaluru. Roles and Responsibilities: Data Analysis & Modeling: Develop and implement machine learning models to address complex business problems. Build predictive models and algorithms to forecast customer behavior, product usage, and business outcomes. Conduct statistical analysis and hypothesis testing to uncover key insights and trends. Data Engineering & Processing: Clean, preprocess, and transform large-scale datasets from multiple sources. Design and optimize data pipelines for both real-time and batch processing. Business Insights & Reporting: Collaborate with business teams to define key performance indicators (KPIs). Develop dashboards and reports to effectively communicate findings and business performance. Present actionable insights and recommendations to stakeholders and leadership teams. Product Improvement: Partner with product managers to integrate data-driven insights into product features. Monitor model performance and continuously improve accuracy and scalability. Run A/B tests to evaluate the impact of product changes and optimize user experience. Research & Development: Stay updated with the latest developments in machine learning, artificial intelligence, and data science. Explore and implement new techniques and tools to drive innovative solutions and improve outcomes. Qualifications: Minimum Experience: 3 years of professional experience in Data Analytics, Data Science, AI, or Machine Learning. Technical Expertise: Deep analytical expertise in applying statistical solutions to business problems. Experience with exploratory data analysis of large datasets using tools like SQL, Hive, Spark, or similar. Proficiency in machine learning and deep learning tools such as Scikit-learn, TensorFlow, PyTorch, and familiarity with techniques like Neural Networks, Gradient Boosting, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines, Clustering, etc. Experience working with visualization tools such as Tableau and Power BI. Business & Innovation: Demonstrated ability to innovate solutions and solve business problems using data science techniques. Desirable Additional Experience: 4+ years of experience in data science or machine learning in a product-focused environment. Experience working with relational or document databases. Proficiency in C, Python, PyTorch, Java, JavaScript, Node.js, React.js, or Vue.js. Strong knowledge of hypothesis testing and regression analysis. Experience in a SaaS product environment. Educational Qualifications: Bachelor s/Master s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.

Job Description You are a strategic thinker passionate about driving solutions in Analytics Solutions. You have found the right team. As an Analytics Solutions Associate in our Finance team, you will spend each day defining, refining and delivering set goals for our firm. You will be responsible for the design, implementation and execution of end-to-end processes supporting U.S. Regulatory Reporting including Consolidated, Capital, Standalone and CCAR/DFAST reporting, regulatory reporting training and exam management. Additionally, FRRA drives broader strategic initiatives across external reporting including accountability, error and issue management, manual adjustments, variance analysis, quality assurance and the target U.S. Regulatory Reporting platform. The FRRA Innovation team sits within FRRA and is responsible for leading the development and implementation of Business Intelligence, Data Analytics and Intelligent automation solutions, identifying and delivering process automation and technology innovation, supporting the reporting production close, and helping to define and design multi-year business infrastructure strategy. Job Responsibilities Implement process automation solutions across the business using Business Intelligence tools. Drive process discovery through partnerships with key stakeholders in the business. Follow established project lifecycle from end to end to deliver timely, efficient, and fit-for-purpose solutions. Engage partners such as FRRA process owners, Center of Excellence teams, and Control partners through established forums. Assist with various aspects of project management including development of project plans, task management, design, testing scenarios and analysis, implementation, and procedural / operating model documentation. Collaborate with system / data owners and business project teams to improve overall data quality and implement tactical solutions to automate repetitive, manual data clean-up and aggregation work. Develop expertise in existing and future strategic data source systems to streamline and improve information content, transparency, and delivery. Communicate summary of analysis and findings thoroughly and succinctly (summary of facts, data sources, analyses performed, conclusions, and recommendations) to various stakeholders, including executive leadership and participate/lead Innovation forums. Stay up-to-date with industry trends and best practices in process automation, analytics, and innovation. Required Qualifications, Capabilities, and Skills Minimum 3 years experience in design and delivery of analytics, reporting and process automation solutions. Advanced data transformation skills using Alteryx and/or Python. Experience with data visualization tools (e.g., Tableau, Power BI) and analytics platforms. Strong project management skills with the ability to manage multiple projects simultaneously. Good analytical and presentation skills. Willingness to learn and adopt new cutting edge technologies, toolsets and techniques. Excellent communication and interpersonal skills, with the ability to collaborate effectively with diverse teams. Preferred Qualifications, Capabilities, and Skills Bachelor's degree in Computer Science, Information Technology, Business Administration, or a related field. Finance experience a plus. Certifications in process automation or data analytics. Knowledge of SQL and/or RPA tools like UIPath. Experience with process review, discovery and reengineering. Understanding of workflow automation tools such as Pega or ServiceNow. Experience in a similar role within a fast-paced, innovative environment. About Us JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. Qualification : Bachelor's degree in Computer Science, Information Technology, Business Administration, or a related field. Finance experience a plus.

Job Title: Business Intelligence (BI) Lead Life Sciences Sector About the Role: As the BI Lead, you will spearhead and develop Business Intelligence (BI) projects within the team, focusing on constructing an analytical data layer, developing custom BI reporting solutions, monitoring platform performance, and enabling self-serve reporting for Regional Business Units (RBU) and Global Business Units (GBU). Your primary responsibility is to deliver high-quality contributions to client projects in the life sciences sector. These tasks will range from basic analysis and problem-solving to assisting in the creation of more complex solutions. You ll demonstrate a comprehensive understanding of pharmaceutical data assets, including IQVIA, CRM, and MCM data, as well as country-specific variations. Key duties include training and upskilling Business Units (BUs) to use the self-serve layer effectively for report and dashboard creation, assessing data requirements for decision-making, and ensuring data accuracy. You ll work closely with engineering and data platform teams to improve data availability and reliability, while collaborating on client proposals and solution strategies. Additionally, you will contribute to documentation and specifications, design presentations, and actively engage in the consulting methodologies and life sciences market to continuously grow your knowledge. Key Responsibilities: Lead BI projects, including building and maintaining an analytical data layer, and developing BI solutions for reporting and visualization. Deliver high-quality, timely contributions to life sciences client projects, ranging from basic analysis to complex solutions. Utilize pharmaceutical data assets (IQVIA, CRM, MCM) and understand regional data variations. Train Business Units (BUs) to efficiently use the self-serve reporting layer for creating reports and dashboards. Assess data requirements, identify suitable data sources, ensure data accuracy, and perform necessary transformations for decision-making. Establish and track business metrics, and perform in-depth process analysis to identify areas for improvement. Collaborate with engineering and data platform teams to enhance data availability and reliability. Review and analyze client requirements, contribute to proposal development, and create tailored client solutions. Create detailed documentation, including specifications and quantitative/qualitative analyses. Present client deliverables within established frameworks, adapting presentations to audience needs. Stay engaged in consulting methodologies, life sciences market trends, and professional development opportunities. Manage project-based responsibilities under the guidance of senior consultants and directors. Desired Candidate Profile: Proficiency in SQL and BI platforms, particularly Power BI (Spotfire knowledge is a plus). Extensive experience with data transformation/ETL, data modeling, and a strong understanding of data platforms and ETL processes. Hands-on experience with Power BI, including the creation of reports, dashboards, and visualizations, and experience in environments such as Salesforce, Snowflake, or Azure. Skilled in migrating SSRS reports/Tabular reports to Power BI Paginated Reports. Advanced knowledge of Power Query M and experience building sophisticated DAX queries. Experience implementing static and dynamic Row Level Security, along with extensive knowledge in dataset design, data cleansing, and aggregation. Understanding of relational database structures, principles, and practices. Solid SQL skills, including the ability to write complex queries and create SQL views for custom datasets. Strong proficiency in Excel, PowerPoint, and Access, with VBA knowledge considered a plus. Proven ability to build relationships with multiple stakeholders (BI engineers, Data Engineers, Consulting teams, Product Managers). Familiarity with Software Development Life Cycle (SDLC) and Agile methodologies. Experience with technical project execution, including proposal writing, creating BRD, PDD, SDD, and user documentation. Excellent verbal and written communication skills. Previous experience in application or implementation support is required. Strong problem-solving skills and a macro-level approach to research and analytics. Good to Have: Experience with other BI technologies (e.g., Tableau, Looker Studio, ThoughtSpot). Knowledge of Python/R. Experience with Microsoft Power Platform tools (e.g., PowerApps, Power Automate). Hands-on experience with Canvas App Configuration, Canvas App Functions, Power Portals, Power Automate Desktop, and custom connectors. Familiarity with Azure services, AI builder, Virtual Agents, and SharePoint list customization. Microsoft Power Platform certification is a plus. Qualifications: Bachelor s or Master s degree in Computer Science, Information Technology, or a related field. 6-8 years of relevant experience. Demonstrated collaborative approach, working effectively across teams to achieve objectives. Knowledge of core business processes and their impact on decision-making and growth. Familiarity with consulting methodologies, tools, and techniques. Up-to-date with current industry trends and insights into competitors and marketplace dynamics. Proficiency in time management, Scrum methodologies, and agile working practices. Qualification : Bachelors or Masters degree in Computer Science, Information Technology, or a related field.

Your Impact As a Data Science Analyst at McKinsey, you will collaborate closely with the Insights & Analytics (IA) group and consulting teams to solve analytically complex client problems in the marketing domain. You will apply advanced analytical and modeling techniques, drawing insights through statistical techniques and predictive modeling to guide marketing efforts. Your primary responsibility will be client service, with an additional focus on knowledge development within the team. Key activities will include: Performing statistical analysis and modeling to support marketing-related client engagements. Developing and refining statistical models aimed at optimizing pricing strategies and promotional activities. Providing guidance to teams on analytics projects, particularly on technique and modeling-related issues. Supporting the development and maintenance of McKinsey s proprietary marketing techniques and contributing to other knowledge development initiatives. Coaching and mentoring new hires by sharing your business, technical, and functional expertise. Delivering high-quality, client-ready end products on time, with attention to detail and performing quality checks as required. Your Growth You will be a key part of McKinsey s Growth, Marketing & Sales (GM&S) team, based in either Gurgaon or Bengaluru, primarily supporting the Insights & Analytics (IA) group of GM&S. This team leverages McKinsey's decades of experience in marketing and sales to help leading companies improve pricing, promotions, assortments, and performance management. The GM&S Solutions team blends cutting-edge software, tailored services, and deep expertise to provide clients with a comprehensive view of their commercial and financial performance. By integrating various data sources into a central data warehouse, the team enables clients to make informed decisions using advanced analytics. McKinsey Solutions fosters innovation in areas such as design thinking, mobile, and social, helping to reshape the consulting model toward asset-based solutions. This is a growing area within McKinsey, with a vibrant ecosystem of alliances, strategic acquisitions, and the development of new products and services that redefine how McKinsey works with clients. As part of McKinsey Solutions, you ll be part of a team of more than 1,000 dedicated professionals, including over 800 analysts and data scientists, working on impactful, innovative solutions. Your Qualifications and Skills Mandatory: Master s degree in Statistics, Economics, Econometrics, Computer Science, Engineering, Mathematics, or an MBA with a strong quantitative background. 2+ years of relevant work experience in analytics, business intelligence, or advanced analytics with an analytics firm. Proficiency in statistical programming software such as Python, and comfortable working with large datasets. Familiarity with R and SQL is also preferred. Experience in handling large volumes of data, including data manipulation, data cleansing, and data matching using tools like R, SQL, and Excel VBA. Strong analytical and problem-solving skills, with the ability to break down complex issues, identify root causes, and recommend actionable solutions. Knowledge of forecasting, regression analysis, and segmentation methodologies. Experience with modeling techniques, including logistic regression, linear regression, cluster analysis, CHAID, and similar approaches. Industry experience in consumer goods, telecom, or retail is a plus. Ability to thrive in a dynamic and evolving environment where priorities change frequently, and methodologies are often challenged. Capacity to work efficiently under pressure and meet tight deadlines. Qualification : Masters degree in Statistics, Economics, Econometrics, Computer Science, Engineering, Mathematics, or an MBA with a strong quantitative background.

Intuit is a global leader in financial technology, dedicated to helping individuals and businesses thrive. Our suite of products, including TurboTax, Credit Karma, QuickBooks, and Mailchimp, serves approximately 100 million customers worldwide. At Intuit, we believe in providing everyone with the tools and resources they need to achieve financial success. We are constantly innovating to make financial empowerment a reality for all. Job Overview Join the Intuit Data Platform (IDP) team as a Staff Engineer and help us transform the way we handle big data! The IDP team is responsible for the Intuit Analytics Platform, which powers real-time data ingestion, cataloging, analytics, and machine learning across the entire organization. As Intuit s customer base grows, so does the volume of data we process. Our engineering excellence ensures that we can scale and leverage this data to drive machine learning and product innovations. We re in the process of building the next-generation real-time and batch ingestion engine, capable of indexing, cataloging, and organizing data and metadata. We are passionate about using open-source technologies to solve challenges and contributing back to the community. If you're excited about building a platform that will directly impact data scientists and analysts and have a desire to shape the future of data at Intuit, then come join us! Key Responsibilities Architect & Design: Build fault-tolerant and scalable big-data platforms using open-source technologies to handle massive datasets. Data Solutions: Create architecture solutions that address complex use cases like data normalization, lineage, governance, ontology, and discoverability. Cross-Team Collaboration: Work with analysts and data scientists to understand data requirements for building operational propensity models and gaining deep customer insights. Hands-On Coding: Lead development efforts within the Hadoop ecosystem using technologies such as Java MapReduce, Spark, Scala, HBase, and Hive to build and optimize data pipelines for both real-time and batch applications. Database Management: Work with NoSQL, SQL, and in-memory databases to design high-performance data systems. Code Reviews: Ensure code quality, consistency, and adherence to best practices through regular code reviews. Architectural Alignment: Ensure alignment between enterprise architecture and business requirements. Prove Feasibility: Conduct proof-of-concept (POC) experiments for new technologies or approaches and drive them to production. Collaboration with Data Cataloging Team: Work closely with data catalog teams and architects to index and catalog all data sources at Intuit. Agile Leadership: Lead fast-paced development teams using agile methodologies and promote best practices in software development, testing, and incident response. Design & Model: Build dimension models suited for customer business use cases and ensure seamless integration of business and technical requirements. Qualifications Experience: 12+ years of relevant experience, with at least 5+ years specializing in the big data domain. Big Data Architecture: Proven experience in architecting end-to-end ecosystems for big data and analytics platforms. Expert Knowledge: Deep expertise in building fault-tolerant, scalable big data solutions, especially using the Hadoop ecosystem (Hive, HBase, Spark, Kafka, MapReduce, etc.). Programming Expertise: Mastery of Java and Scala, with a focus on building high-throughput data services. Machine Learning: Knowledge of machine learning principles and AI applications in big data. Big-Data Technologies: Familiarity with tools such as HDFS, Storm, Zookeeper, Cassandra, Redshift, GraphDB, and others. Understanding both real-time and batch processing in the Hadoop ecosystem. Communication: Strong communication skills, with an ability to explain complex technical topics to both technical and non-technical audiences. Programming Skills: Intermediate experience in Python or R for data processing. Education: BE/BTech/MS in Computer Science or a related field (or equivalent experience). Collaboration: Demonstrated ability to work cross-functionally and lead change through influence and example. At Intuit, you ll be part of a talented, passionate team working on innovative solutions that shape the future of data analytics and machine learning. As a Staff Engineer, you ll have the chance to work with cutting-edge technologies, build scalable systems, and help revolutionize how Intuit leverages data to drive product innovation. If you're looking for a dynamic environment where you can have a meaningful impact, come join us at Intuit! Qualification : BE/BTech/MS in Computer Science (or equivalent)

Job Title: Sr. Engineering Manager - Data Engineering Level: L5 Experience: 13-16 years Overview We are seeking an experienced Engineering Manager with a strong background in Data Engineering, including ETL/ELT processes and cloud-based data platforms such as Snowflake. The ideal candidate will lead and mentor a team of data engineers, drive data architecture initiatives, and work closely with cross-functional stakeholders to ensure our data infrastructure supports evolving business needs. Key Responsibilities Team Leadership: Lead, mentor, and develop a high-performing data engineering team, fostering a culture of collaboration, innovation, and continuous learning. Data Pipeline Development: Oversee the design, development, and maintenance of robust ETL/ELT pipelines to ingest, transform, and process data at scale. Cloud Data Infrastructure: Drive the architecture and implementation of cloud-based data solutions, especially leveraging Snowflake, ensuring scalability, security, and reliability. Cross-Functional Collaboration: Partner with product managers, analysts, data scientists, and other business stakeholders to gather requirements and prioritize engineering efforts that deliver the most impact. Architecture and Design: Develop and enforce data architecture standards for high-performance data warehousing, ensuring seamless data integration across diverse sources. Performance Optimization: Identify and resolve performance bottlenecks, focusing on query optimization, cost management, and resource efficiency. Data Quality & Governance: Define and implement data quality frameworks and governance practices, ensuring data consistency and reliability across all pipelines. Innovation & Strategy: Stay informed on emerging data technologies and industry best practices, continuously improving processes and aligning solutions with long-term data strategies. Required Skills 8+ years of hands-on experience in data engineering, including 5+ years in a leadership role. Strong expertise in ETL/ELT processes and hands-on experience with tools like Talend, Informatica, or similar platforms. Deep proficiency in Snowflake or comparable cloud data platforms such as Redshift or BigQuery. Advanced SQL skills, including query optimization, performance tuning, data modeling, and schema design. Hands-on experience with Python or Java for data processing and automation. Knowledge of data governance, compliance standards, and data security best practices. Excellent communication and project management skills, with the ability to prioritize and manage multiple projects in parallel. Preferred Skills Exposure to Big Data technologies such as Spark, Hadoop, Databricks, Synapse, etc. Experience with workflow orchestration tools like Apache Airflow or AWS Step Functions. Familiarity with CI/CD pipelines and DevOps practices within data engineering. Experience working with BI tools like Tableau or Power BI, and reporting integrations.

Data Engineer Role Overview We are looking for a Data Engineer to design, develop, and maintain scalable data pipelines and ETL processes. You will work closely with data scientists, analysts, and engineers to ensure efficient data processing and storage solutions that support business intelligence and analytics needs. This role requires expertise in SQL, big data technologies, and cloud platforms to build and optimize data workflows. Key Responsibilities Data Pipeline Development & Optimization Design and build scalable ETL/ELT processes for structured and unstructured data. Develop and maintain data ingestion frameworks to handle large datasets efficiently. Ensure data integrity, consistency, and security across multiple sources. Database & Data Warehouse Management Develop, optimize, and maintain relational and NoSQL databases. Implement data modeling best practices for performance and scalability. Work with cloud-based data warehouses (e.g., Snowflake, Redshift, BigQuery). Big Data & Cloud Technologies Leverage big data tools (e.g., Spark, Hadoop, Databricks) for data processing. Work with cloud platforms (e.g., AWS, Azure, GCP) to build and optimize data solutions. Develop real-time and batch processing workflows. Collaboration & Documentation Work closely with data scientists, engineers, and business teams to understand data requirements. Document data pipelines, architecture, and workflows for scalability and maintenance. Required Qualifications & Skills Technical Expertise: Strong experience with SQL and Python for data processing. Proficiency in ETL/ELT frameworks and data integration techniques. Hands-on experience with big data tools (e.g., Apache Spark, Hadoop, Kafka). Cloud & Database Management: Expertise in cloud data platforms (Azure, AWS, GCP). Experience with data warehousing solutions (Snowflake, Redshift, BigQuery). Understanding of data governance, security, and compliance. Performance Optimization & Troubleshooting: Ability to optimize SQL queries and improve data processing efficiency. Experience troubleshooting complex data pipeline issues. Apply Now & Be Part of an Innovative Data Team!

Skills Required: Should have a minimum 6+ years in Data Engineering, Data Analytics platform. Should have strong hands-on design and engineering background in AWS, across a wide range of AWS services with the ability to demonstrate working on large engagements. Should be involved in Requirements Gathering and transforming them to into Functionally and technical design. Maintain and optimize the data infrastructure required for accurate extraction, transformation, and loading of data from a wide variety of data sources. Design, build and maintain batch or real-time data pipelines in production. Develop ETL/ELT Data pipeline (extract, transform, load) processes to help extract and manipulate data from multiple sources. Automate data workflows such as data ingestion, aggregation, and ETL processing and should have good experience with different types of data ingestion techniques: File-based, API-based, streaming data sources (OLTP, OLAP, ODS etc) and heterogeneous databases. Prepare raw data in Data Warehouses into a consumable dataset for both technical and non-technical stakeholders. Strong experience and implementation of Data lakes, Data warehousing, Data Lakehousing architectures. Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures. Monitor data systems performance and implement optimization strategies. Leverage data controls to maintain data privacy, security, compliance, and quality for allocated areas of ownership. Experience of AWS tools (AWS S3, EC2, Athena, Redshift, Glue, EMR, Lambda, RDS, Kinesis, DynamoDB, QuickSight etc.). Strong experience with Python, SQL, pySpark, Scala, Shell Scripting etc. Strong experience with workflow management & Orchestration tools (Airflow, Should hold decent experience and understanding of data manipulation/wrangling techniques. Demonstrable knowledge of applying Data Engineering best practices (coding practices to DS, unit testing, version control, code review). Big Data Eco-Systems, Cloudera/Hortonworks, AWS EMR etc. Snowflake Data Warehouse/Platform. Streaming technologies and processing engines, Kinesis, Kafka, Pub/Sub and Spark Streaming. Experience of working with CI/CD technologies, Git, Jenkins, Spinnaker, Ansible etc Experience building and deploying solutions to AWS Cloud. Good experience on NoSQL databases like Dynamo DB, Redis, Cassandra, MongoDB, or Neo4j etc. Experience with working on large data sets and distributed computing (e.g., Hive/Hadoop/Spark/Presto/MapReduce). Good to have working knowledge on Data Visualization tools like Tableau, Amazon QuickSight, Power BI, QlikView etc. Experience in Insurance domain preferred.