BIG Data Engineer Jobs

Sr. Big Data Engineer Location: India The Impact You Will Have: You will work on a variety of impactful customer technical Big Data projects, which may include building reference architectures, how-to's and production-grade MVPs. Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications. Consult on architecture and design; bootstrap or implement strategic customer projects that lead to a customer's successful understanding, evaluation and adoption of Databricks. Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement-specific product and support issues. What We Look For: 10+ years experience with Big Data Technologies such as Apache Spark , Kafka, Cloud Native and Data Lakes in a customer-facing post-sales, technical architecture or consulting role. 6+ years of experience working on Big Data Architectures independently. Strong experience working in the Databricks ecosystem. Comfortable writing code in either Python or Scala. Experience working across Cloud Platforms (GCP / AWS / Azure). Documentation and white-boarding skills. Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects. About Databricks: Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake, and MLflow. Benefits: At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.

Senior Data Engineer Hyderabad (On-site, Full-time) Location: Hyderabad, Telangana Work Type: On-site, Full-time Experience: 5+ Years Industry: AI & Data Science Company: Blend About Blend: Blend is a leading AI services company focused on solving real-world problems through the fusion of artificial intelligence, data science, and human ingenuity. We believe in co-creating meaningful impact by aligning top-tier talent with cutting-edge technology. Our goal is to deliver transformative solutions that unlock value for our clients and enrich the work and lives of our people. Job Overview: We are seeking a highly skilled Senior Data Engineer with strong experience in AWS, Databricks, Python, SQL, and Apache Spark/PySpark. You will be responsible for designing, developing, and maintaining scalable data architectures and pipelines to support analytics, machine learning, and business intelligence efforts across the organization. Key Responsibilities: Design and build scalable data pipelines using AWS services (Glue, Lambda, S3, EMR) and Databricks Notebooks & Workflows. Develop and manage robust ETL/ELT workflows using Python and SQL to handle structured and semi-structured data. Implement distributed data processing using Apache Spark or PySpark. Create and maintain data lakes in AWS Databricks. Collaborate with data scientists, analysts, and cross-functional teams to provide high-quality, accessible datasets. Ensure adherence to data governance, quality, and security best practices. Monitor, troubleshoot, and optimize the performance of data systems. Conduct code reviews and enforce engineering best practices. Mentor junior engineers and support their technical growth. Required Qualifications: Bachelor's or Master s degree in Computer Science, Engineering, or related field. 5+ years of experience in Data Engineering, with 2+ years working in AWS Databricks environments. Strong programming skills in Python for data processing and workflow automation. Advanced expertise in SQL for data transformation and querying large datasets. Proficient in distributed data processing using Apache Spark/PySpark. Solid understanding of data modeling, data warehousing, and performance optimization techniques. Hands-on experience with AWS services such as Glue, S3, Lambda, and EMR. Familiarity with version control tools like Git or CodeCommit. Experience with workflow orchestration tools like Airflow or AWS Step Functions (preferred but not mandatory). Be part of a forward-thinking, AI-driven organization. Work with cutting-edge cloud technologies and data platforms. Thrive in a culture of innovation, mentorship, and continuous learning. Enjoy opportunities to grow technically and professionally while driving real-world impact. Apply Now to join Blend as a Senior Data Engineer and help build data infrastructure that powers intelligent decision-making. Qualification : Bachelor's or Masters degree in Computer Science, Engineering, or related field.

Job Title: Azure Data Engineer Location: Hyderabad / Bangalore (Hybrid) Job Type: Full-time Salary: Negotiable Position Overview: We are looking for an Azure Data Engineer with 5-8 years of experience to join our team. As an Azure Data Engineer, you will design, implement, and manage data solutions on the Microsoft Azure cloud platform. The ideal candidate will have a strong background in writing complex SQL stored procedures, implementing OLTP database solutions using Microsoft SQL Server, and working with Azure Synapse, PySpark, and Azure Databricks for big data processing. Key Responsibilities: Data Integration and Collaboration: Collaborate with cross-functional teams to gather, analyze, and document business requirements for data integration projects. Complex SQL Expertise: Write and optimize complex T-SQL, Dynamic SQL, and Spark SQL queries, including the creation of stored procedures for data transformation and business validation logic. Big Data Processing: Utilize Azure Synapse/Databricks to write notebooks using Spark SQL or PySpark for processing and analyzing large volumes of data. Data Pipeline Development: Develop and maintain robust data pipelines using Azure Data Factory to ensure seamless data flow across systems. OLTP Systems: Contribute to the enhancement and optimization of OLTP systems using SQL Server. Data Quality and Integrity: Ensure data quality, integrity, and accuracy in all systems. Programming and Algorithm Development: Utilize strong algorithmic programming skills to handle data processing and transformation. Qualifications: Educational Background: Bachelor s degree in Computer Science, Information Technology, or a related field. Experience: 5-8 years of experience in database development, data integration, and writing complex T-SQL queries. Technical Skills: Expertise in T-SQL and Spark SQL/PySpark (experience with Azure Synapse and Databricks is essential). Hands-on experience with Azure Data Factory for building data pipelines. Strong experience with OLTP systems using SQL Server. Problem-Solving Skills: Excellent problem-solving abilities with a strong focus on attention to detail. Adaptability: Ability to work in a collaborative and fast-paced environment, focusing on delivering high-quality solutions. Other Details: Notice Period: 0-15 days MAX Work Location: Hyderabad / Bangalore (Hybrid) If you're an experienced Azure Data Engineer with a passion for big data and cloud technologies, apply now to join our team and make an impact with innovative data solutions! Qualification : Bachelors degree in Computer Science, Information Technology, or a related field.

About the Job Like Google's own ambitions, the work of a Software Engineering Manager goes far beyond Search. This role combines technical leadership with team management to drive large-scale, impactful projects while enabling your team of engineers to deliver their best work. You ll not only contribute to product strategy and manage project goals but also foster the growth of talented engineers across your team. Google s engineering teams tackle challenges in information retrieval, artificial intelligence, distributed computing, large-scale system design, networking, security, and data analytics, among others. As a manager, you will lead engineering teams across multiple locations and drive high-impact solutions for complex challenges. Our Enterprise Data & Engineering (EDE) team is focused on unlocking the value of enterprise data, making it accessible, reliable, secure, and actionable for Googlers. Corp Eng builds business solutions that scale globally to support Google s internal operations and services. Our mission is simple: We are Google for Googlers delivering tools and experiences that help every Googler create impactful products and services. Responsibilities Conceive and deliver data management and analytics solutions to meet Googlers' needs, driving high-impact projects across Google. Influence Connected Data strategy, ensuring consistent and secure data assets built on canonical entity schema for higher-level insights. Ensure data integrity and security, implementing procedures to maintain the highest levels of confidentiality and data protection. Partner with internal teams to define and implement solutions that improve business processes. Maintain the highest standards of development practices, including technical design, systems configuration, testing, and writing clean, modular code. Minimum Qualifications Bachelor's degree or equivalent practical experience. 8 years of experience in software development using one or more programming languages (e.g., Python, C, C++, Java, JavaScript). 3 years of technical leadership experience overseeing projects, with 2 years in people management or team leadership. Experience in data management, data integration, distributed databases, and SQL pipelines. Preferred Qualifications Master s degree or PhD in Computer Science or a related technical field. Experience implementing and integrating third-party applications in domains like Finance, Supply Chain, HR, and Marketing.

General Summary: Qualcomm is at the forefront of technological innovation, leveraging data-driven insights to power business decisions. We are seeking a Senior/Lead Data Engineer to design, develop, and implement advanced data solutions to support Qualcomm s business goals. This role will involve building scalable data pipelines, integrating large datasets, and collaborating with cross-functional teams to unlock the value of data. As a key technical leader, you will help shape Qualcomm s data infrastructure and work closely with data scientists, analysts, and business stakeholders to ensure the delivery of reliable and high-quality data solutions. Key Responsibilities: Design and implement scalable data pipelines and ETL processes for structured and unstructured data. Develop and optimize data lake, data warehouse, and real-time data processing solutions. Collaborate with data scientists, analysts, and product teams to understand data requirements and translate them into robust data solutions. Ensure data quality, reliability, and security across all data systems and pipelines. Build and maintain data models that support business intelligence and advanced analytics needs. Optimize data workflows for performance, scalability, and cost-efficiency. Provide technical leadership and mentorship to junior data engineers. Stay up to date with emerging technologies and recommend solutions to improve data architecture. Minimum Qualifications: Bachelor s or Master s degree in Computer Science, Information Systems, Engineering, or related field. 5+ years of experience in data engineering or related roles. Proficiency in Python, SQL, and Scala, with experience in building scalable ETL pipelines. Strong experience with big data technologies (e.g., Hadoop, Spark, Kafka). Hands-on experience with cloud platforms (e.g., AWS, Azure, GCP) and data warehousing solutions (e.g., Redshift, BigQuery, Snowflake). Solid understanding of data modeling, data architecture, and real-time data processing. Experience with CI/CD, containerization (Docker, Kubernetes), and DevOps practices. Preferred Qualifications: Knowledge of machine learning pipelines and working with data science teams. Experience with streaming data frameworks (e.g., Apache Flink, Spark Streaming). Strong understanding of data governance, compliance, and security best practices. Excellent problem-solving, communication, and team collaboration skills. Why Join Qualcomm? At Qualcomm, you ll work on cutting-edge projects, collaborating with global teams to solve challenging problems. We offer: Continuous learning and growth opportunities. Flexible working arrangements and a supportive work culture. The chance to work with innovative technologies and industry leaders.

About HSBC If you re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you're aiming to reach the top or seeking an exciting new direction, HSBC offers opportunities, support, and rewards to take you further. As one of the largest banking and financial services organizations globally, with operations across 64 countries and territories, HSBC is committed to enabling businesses to thrive, economies to prosper, and ultimately, helping people fulfill their ambitions. The Role We are seeking an experienced Senior Software Engineer to join our team. You will become part of HSBC s Data Provisioning Technologies team, responsible for managing and working on the cutting edge of CDP (Cloudera Data Platform) and ODP (Open Data Platform) platforms. As part of one of the largest Big Data estates in the banking industry, you will be instrumental in creating engineering solutions for Hadoop platform pipelines and utilizing industry-leading cloud technologies. Responsibilities Contribute to Hadoop Engineering tasks, developing solutions for data pipeline management on CDP/ODP platforms. Work with Python, Ansible, and Kubernetes to create scalable, efficient solutions within a Big Data environment. Collaborate with the Data/Analytics teams to ensure the smooth operation of data systems and platforms. Design and implement technical solutions while adhering to best practices for CI/CD, DevOps, and GitOps methodologies. Develop and support solutions utilizing cloud technologies, ensuring the scalability and robustness of platforms. Contribute to debugging, troubleshooting, and maintaining the high-quality performance of data systems. Utilize Shell scripting, YAML, and modern automation tools to improve deployment and operational efficiency. Work with GitHub, Jenkins, Ansible for version control, continuous integration, and deployment. Requirements To be successful in this role, you should meet the following requirements: 3-6 years of experience in Hadoop Engineering with practical expertise in Python, Ansible, and DevOps methodologies. Strong knowledge of HDP (Hadoop Distribution), CDP, Linux, Python, Ansible, and Kubernetes. Proficient in Shell scripting, YAML, and technical design. Strong understanding of CI/CD concepts and hands-on experience with tools like GitHub, Jenkins, and Ansible. Familiarity with Test automation tools such as JUnit, Selenium, and Cucumber. Experience with industry-leading Cloud technologies and hands-on development in cloud environments. Working knowledge of GitOps and DevSecOps principles. Knowledgeable in Agile methodologies and ideally, certified in one of the frameworks. Strong communication and networking skills, with the ability to collaborate across teams. Ability to work autonomously, take accountability, and drive results in a high-pressure environment. A strong commitment to high-quality standards, and ownership of individual contributions. You ll have the opportunity to work on innovative projects at the forefront of the banking industry. A global platform with exposure to diverse teams and technologies. Join a company committed to professional development and career growth. Achieve more when you join HSBC. Qualification : 3-6 Years Experience in Hadoop Engineering with working experience on Python, Ansible DevOps methodologies.

Job Overview Senior Engineer - Data Engineering in the Automotive domain with 3-7 years of experience Extensive expertise in pyspark, hadoop, and gcp for designing and implementing data pipelines Proficient in tensorflow, python, and SQL for automation, data quality, and optimization Skilled in big data technologies like numpy, pandas, and data manipulation Responsible for architecting scalable data pipelines, data transformation, performance optimization, monitoring, and collaboration with cross-functional teams Bachelor's degree in Computer Science or equivalent; preferred certifications include Professional Data Engineer and Google Cloud Certified - Professional Data Engineer Good to have experience with CI/CD practices, data processing libraries, data quality, Pub/Sub architectures, and Tekton pipelines management Roles & Responsibilities Architect and Develop Data Pipelines: Lead the design, development, and maintenance of scalable and efficient data pipelines using GCP services like Pub/Sub for real-time data ingestion and BigQuery for storage and analysis. Data Transformation and Processing: Implement data transformation processes to cleanse, enrich, and aggregate raw data from diverse sources, ensuring data quality and consistency. Performance Optimization: Fine-tune data pipelines and queries to enhance performance, reduce latency, and ensure timely data access for stakeholders. Monitoring and Maintenance: Implement monitoring solutions for tracking pipeline performance, addressing issues proactively, and conducting regular maintenance tasks to uphold data infrastructure reliability. Collaboration: Collaborate with Data Scientists, Software Engineers, and Business Analysts to understand data requirements and provide technical solutions to meet business needs. Documentation: Document data pipelines, processes, and best practices to facilitate knowledge sharing and maintain a comprehensive understanding of data architecture. Our ideal candidate Extensive knowledge and proficiency in pyspark, hadoop, and gcp Advanced skills in designing and implementing data pipelines, data modeling, and data warehousing solutions Proficiency in tensorflow and python for automation scripts and data quality Strong SQL skills for querying and optimizing data warehouse operations Expertise in big data technologies like numpy, pandas, and libraries for data manipulation and analysis Monitoring data processes, utilizing GCP services, and implementing data engineering best practices Prioritizing skills in GCP, BigQuery, Python, Data Modeling, SQL, and Data Warehousing Bachelor of Technology (B.Tech) or Bachelor of Engineering (B.E) in Computer Science or Information Technology, or a Master of Technology (M.Tech) in Data Science or Big Data Analytics Certifications such as Professional Data Engineer and Google Cloud Certified - Professional Data Engineer preferred Company overview Altimetrik delivers outcomes for our clients by rapidly enabling digital business & culture and infuse speed and agility into enterprise technology and connected solutions. We are practitioners of end-to-end business and technology transformation. We tap into an organization s technology, people, and assets to fuel fast, meaningful results for global enterprise customers across financial services, payments, retail, automotive, healthcare, manufacturing, and other industries. Founded in 2012 and with offices across the globe, Altimetrik makes industries, leaders and Fortune 500 companies more agile, empowered and successful.Altimetrik helps get companies get unstuck . We re a technology company that lives organizations a process and context to solve problems in unconventional ways. We re a catalyst for organization s talent and technology, helping teams push boundaries and challenge traditional approaches. We make delivery more bold, efficient, collaborative and even more enjoyable. Qualification : Bachelor of Technology (B.Tech) or Bachelor of Engineering (B.E) in Computer Science or Information Technology, or a Master of Technology (M.Tech) in Data Science or Big Data Analytics

We are seeking a highly experienced Senior Big Data Software Engineer to join our dynamic team and tackle challenging projects that will enhance your skills and career. As a Senior Engineer, your contributions will be critical in designing and implementing Big Data solutions across a variety of projects. The ideal candidate will possess deep experience in Big Data and associated technologies, with a strong emphasis on Apache Spark, Python, Azure and AWS. Technologies Hadoop Hive Responsibilities Develop and execute end-to-end Big Data solutions to meet complex business needs Work collaboratively with interdisciplinary teams to comprehend project needs and deliver superior software solutions Apply your expertise in Apache Spark, Python, Azure and AWS to create scalable and efficient data processing systems Maintain and enhance the performance, security, and scalability of Big Data applications Keep abreast of industry trends and technological advancements to foster continuous improvement in our development practices Requirements 5-8 years of direct experience in Big Data and related technologies Advanced knowledge and hands-on experience with Apache Spark High-level proficiency with Hadoop and Hive Proficiency in Python Prior experience with AWS and Azure native Cloud data services We offer Opportunity to work on technical challenges that may impact across geographies Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications Opportunity to share your ideas on international platforms Sponsored Tech Talks & Hackathons Unlimited access to LinkedIn learning solutions Possibility to relocate to any EPAM office for short and long-term projects Focused individual development Benefit package: Health benefits Retirement benefits Paid time off Flexible benefits Forums to explore beyond work passion (CSR, photography, painting, sports, etc.) Qualification : 5-8 years of direct experience in Big Data and related technologies

Data Engineer Location: Bangalore Company: Capital One India About Capital One At Capital One, we're redefining how technology solves real-world financial challenges. As a technology-driven company, we bring together talented engineers, data scientists, and designers to innovate at scale and deliver meaningful impact to millions of customers. If you're passionate about building powerful data solutions, exploring cutting-edge technologies, and working in a collaborative, fast-paced environment this is the place for you. About the Role As a Data Engineer at Capital One, you ll join a team of innovators who design and build next-generation data platforms and pipelines that power real-time decision-making. You ll collaborate across disciplines engineering, product, machine learning, and cloud infrastructure to transform how we leverage data at scale. What You ll Do Collaborate across Agile teams to design, develop, test, and deploy data-driven solutions. Build and support scalable data pipelines using modern data engineering tools and cloud services. Work on real-time and batch data processing systems that integrate with distributed microservices and ML platforms. Use programming languages such as Python, Java, or Scala with SQL, NoSQL, and cloud data warehouses like Redshift or Snowflake. Contribute to code reviews, unit testing, and performance optimization to ensure high-quality data systems. Partner with product managers and platform teams to deliver robust, cloud-native data solutions that power business decisions. Stay ahead of tech trends, share knowledge, and mentor junior engineers. Basic Qualifications Bachelor s degree in Computer Science, Engineering, or a related field. 1.5+ years of hands-on experience in application or data engineering (excluding internships). At least 1 year of experience working with big data technologies. Preferred Qualifications 3+ years of application/data engineering experience using Python, Scala, Java, or SQL. 1+ year of experience with cloud platforms (AWS, Azure, or GCP). 2+ years of experience with distributed computing tools (Spark, Hadoop, Hive, EMR, Kafka, etc.). 1+ year working on real-time streaming applications. 1+ year of experience with NoSQL databases (MongoDB, Cassandra). 1+ year of experience with data warehousing (Redshift, Snowflake). 2+ years working with Linux/Unix systems and shell scripting. Familiarity with Agile methodologies and modern DevOps practices. Why Join Capital One Work on high-impact data solutions at one of the world s most innovative financial institutions. Be part of a collaborative tech culture that values experimentation and learning. Access to top-tier tools, mentorship, and career development opportunities. Competitive compensation and benefits in a mission-driven environment. Qualification : Bachelors degree in Computer Science, Engineering, or a related field

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.

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.

Sr. Data Engineer - AWS - Big Data Location:Bangalore Type of Employment: Full-Time Experience Required: 7 to 10 years Job Overview: We are seeking a highly skilled Sr. Data Engineer with expertise in AWS cloud technologies and Big Data to join our Cloud Data Architect Team at Infocepts. In this critical role, you will design and implement robust data solutions using technologies like EMR, Athena, PySpark, AWS Lambda, S3, and other AWS services. The ideal candidate will have a strong foundation in database concepts and SQL and will be responsible for building scalable data pipelines to support high-performance data processing. Key Responsibilities: Technology Assessment and Design: Study the existing technology landscape and evaluate current data integration frameworks. Assist in designing complex Big Data use cases leveraging AWS services. Documentation and Stakeholder Communication: Prepare and maintain comprehensive project documentation, adhering to quality guidelines and schedules. Work closely with Architects and Project Managers to provide accurate estimations, scoping, and scheduling assistance. Clearly communicate design decisions and conduct Proof-of-Concepts to validate new solutions before implementation. Process Improvement and Automation: Identify areas for process automation to improve efficiency and team productivity. Provide expert guidance and troubleshooting support to junior Data Engineers. Training and Knowledge Sharing: Develop and deliver technology-focused training sessions for the team, ensuring continuous knowledge sharing. Share expertise through Expert Knowledge Sharing sessions with Client Stakeholders. Essential Skills: AWS Services Expertise: In-depth knowledge of S3, EC2, EMR, Athena, AWS Glue, and Lambda. Big Data Technologies: Proficiency with Apache Spark, Databricks, and Big Data table formats such as Delta Lake (open-source). Data Warehousing: Strong understanding of data warehousing concepts and architectures. Programming Skills: Advanced programming skills in Python for building data pipelines. SQL Expertise: Strong SQL skills for data transformation, aggregation, and querying large datasets. ETL Workflow Development: Expertise in creating ETL workflows with complex transformations (e.g., SCD, deduplication, aggregation). Orchestration Tools: Familiarity with orchestration tools like Apache Airflow. MPP Databases: Experience with at least one MPP database (e.g., AWS Redshift, Snowflake, SingleStore). Cloud Databases: Exposure to cloud databases like Snowflake or AWS Aurora. Desirable Skills: Cloud Databases: Familiarity with Snowflake, AWS Aurora. Big Data Technologies: Experience with Hadoop and Hive. AWS Certification: Associate or Professional Level AWS Certification. Advanced Knowledge of Big Data Solutions: Exposure to big data tools and frameworks on cloud platforms. Qualifications: Experience: 7+ years of overall IT experience, with 5+ years specifically focused on AWS-related projects. Educational Background: Bachelor's degree in Computer Science, Engineering, or a related field (Master's degree is a plus). Technical Certifications: Demonstrated commitment to continuous learning through certifications or relevant training. Qualities: Strong analytical and problem-solving skills to deep dive into complex technical challenges.

Position: Cloud Data Engineer AWS Big Data Location: Bangalore, India Employment Type: Full-time Experience Required: 5 to 8 years Purpose of the Position: Join the Infocepts Cloud Data Architect Team as a Cloud Data Engineer and help design and implement cutting-edge big data solutions on AWS. You will leverage your expertise in EMR, Athena, PySpark, S3, AWS Lambda, and SQL to develop robust and scalable data platforms. Key Responsibilities: Technology Assessment and Design: Assess existing technology landscape and data integration frameworks. Design complex Big Data use cases using AWS services under guidance of the Architect. Support architectural decision-making by evaluating trade-offs in cost, performance, and durability. Recommend optimizations to existing data infrastructure. Documentation and Stakeholder Communication: Create project documentation adhering to quality and delivery standards. Collaborate closely with Architects and Project Managers for scoping, estimation, and planning. Present design decisions to technical and business stakeholders clearly. Conduct PoCs and design review sessions. Process Improvement and Automation: Identify and suggest opportunities for automation and process enhancements. Mentor junior engineers and support technical problem solving. Training and Knowledge Sharing: Prepare and deliver internal training on AWS and Big Data topics. Lead client knowledge sharing sessions and contribute to case studies. Essential Skills: In-depth experience with AWS services: S3, EC2, EMR, Athena, Glue, Lambda Familiarity with MPP databases like Redshift, Snowflake, or SingleStore Proficiency in Apache Spark and Databricks Strong programming skills in Python Experience building data pipelines using AWS and Databricks Knowledge of Big Data file formats such as Delta Lake Advanced SQL skills for large-scale data manipulation Hands-on experience with Apache Airflow or similar orchestration tools Strong understanding of ETL workflows and data warehousing concepts Desirable Skills: Cloud databases: AWS Aurora, Snowflake Experience with Hadoop and Hive AWS Certifications (Associate or Professional level) are a plus Qualifications: Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) Overall 5+ years of IT experience with at least 3 years in AWS Big Data projects Ongoing learning and technical certifications are strongly encouraged Key Qualities: Strong problem-solving and analytical thinking Self-driven with a passion for emerging data technologies Excellent communication and client presentation skills Ability to work in cross-functional, agile teams Apply now to be part of a high-impact data transformation team working on large-scale cloud data projects! Qualification : Bachelors degree in Computer Science, Engineering, or related field (Masters preferred)

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: Senior Solutions Engineer (Analytics, AI, Big Data, Public Cloud) Job Summary As a Senior Solutions Engineer (Analytics, AI, Big Data, Public Cloud), you will guide the technical evaluation phase in a hands-on environment throughout the sales process. You will be a technical advisor internally to the sales team and work with the product team as an advocate of your customers in the field. You will help our customers achieve tangible data-driven outcomes through the use of our Databricks Lakehouse Platform, helping data teams complete projects and integrate our platform into their enterprise Ecosystem. You'll grow as a leader in your field while finding solutions to our customers' biggest challenges in big data, analytics, data engineering, and data science problems. You will report to the Solutions Architect (SA) Manager. The Impact You Will Have You will be a Big Data Analytics expert on aspects of architecture and design. Engage with the technical community by leading presentations, workshops, seminars, and meet-ups. Lead your clients through evaluating and adopting Databricks, including hands-on Spark programming and integration with the wider cloud ecosystem. Support your customers by authoring reference architectures, how-tos, and demo applications. Integrate Databricks with 3rd-party applications to support customer architectures. Together with your Account Executive, you will form successful relationships with clients throughout your assigned territory to provide technical and business value. What We Look For Consulting, pre-sales, or post-sales experience working with external clients across a variety of industry markets. Core strength in either data engineering or data science is advantageous. 5+ years of experience demonstrating technical concepts, including presenting and white-boarding. 4+ years of experience designing architectures within a public cloud (AWS, Azure, or GCP). 4+ years of experience with Big Data technologies, including Spark, AI, Data Science, Data Engineering, Hadoop, Cassandra, and others. Solid coding experience in Python, R, Java, Spark, or Scala. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake, and MLflow. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook.

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.

Job Description Job Description:The Intel Foundry Manufacturing and Supply chain FMSC Automation team is looking for a highly motivated Big Data Engineer with strong data engineering skills for data integration of various manufacturing data. You will be responsible for engaging with customers and driving development from ideation to deployment and beyond. This position is a technical role that requires the direct design and development of robust, scalable, performant systems for world-class manufacturing data engineering.Responsibilities include:Create and maintain optimal data architectureAssemble large, complex data sets that meet functional and non-functional business requirementsIdentify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sourcesWork with stakeholders including the users, cross functional teams to assist with data-related technical issues and support their data infrastructure needs.Standard process to keep data secure with right access and authorizationFocus on automated testing and robust monitoringThe ideal candidate must exhibit the following behavioral traits:Excellent problem solving and interpersonal communication skillsStrong desire to learn and share knowledge with others.Be inquisitive, innovative, and a team player with a strong focus on quality workmanship.Troubleshooting skills and root cause analysis for performance issuesAbility to lean, adopt and implement new skills to drive innovation and excellence.Ability to work with cross functional teams in dynamic environment Qualifications Minimum Qualifications: A bachelor's with 4+ years of experience in related field Experience building and optimizing big data pipelines Experience with skills pf handling unstructured data Experience with data transformations, structures, metadata, workload management Experience with big data tools: Spark, Kafka, NIFI, etc. Experience with at least programming languages: Python, C#, .NET Experience with relational SQL and NOSQL DBs Experience in leveraging open-source packages Experience in cloud native skills such as Docker, Kubernetes, Rancher etc. Good to have skills:Experience with semiconductor manufacturingExperience of data engineering on cloudExperience in developing AI/ML Solutions Inside this Business Group As the world's largest chip manufacturer, Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology Development and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore s Law to bring smart, connected devices to every person on Earth. Posting Statement All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance. Qualification : A bachelor's with 4+ years of experience in related field

Data Engineer Big Data Job Location: Nagpur Experience Required: 5 to 7 years Positions Open: 3 Shift: Rotational Shift Job Overview: We are looking for a talented Data Engineer with expertise in Big Data technologies to join our growing team. As a Data Engineer, you will be responsible for expanding and optimizing our data pipeline architecture. You will work closely with software developers, database architects, data analysts, and data scientists to ensure the seamless flow of data across various systems. This role requires proficiency in Hadoop, Hive, Spark, and other big data technologies, as well as solid experience in data transformation and ETL processes. If you are passionate about building and optimizing data systems, this is the role for you! Key Responsibilities: Data Pipeline Architecture: Expand and optimize the architecture for data flow and collection across various teams. Big Data Technologies: Work with Hadoop ecosystem tools such as Hive, Sqoop, and Spark to process large datasets. SQL Optimization: Craft and optimize complex SQL queries for data transformation, aggregation, and analysis. Python Programming: Use Python (including libraries like Pandas and NumPy) to process and manipulate data efficiently. ETL Processes: Ensure smooth data movement and transformation by applying industry best practices in ETL. Data Warehousing: Apply knowledge of data warehousing concepts to optimize data storage and retrieval. Data Quality Management: Troubleshoot data-related issues, ensuring the quality, consistency, and integrity of data. Collaboration: Work closely with cross-functional teams, translating complex technical concepts to non-technical stakeholders. Cloud Integration: Use cloud platforms (e.g., AWS, Azure, GCP) to integrate data systems and services. Automation: Write and maintain shell scripts or other automation tools for efficient data processing. Documentation: Create clear, concise technical documentation to facilitate knowledge sharing and communication across teams. Required Skills and Qualifications: 5 to 7 years of experience in Data Engineering, with a focus on Big Data technologies. Proficiency in SQL for data manipulation and analysis. Strong programming skills in Python (Pandas, NumPy) for data processing and manipulation. Hands-on experience with big data tools such as Hadoop, Hive, Sqoop, and Spark. In-depth understanding of ETL processes and data transformation methodologies. Experience in designing data models and optimizing data storage in data warehouses. Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and their data engineering services is a plus. Ability to write shell scripts or other automation scripts for data processing. Ability to troubleshoot data-related issues and ensure data quality and consistency. Strong collaboration skills in a cross-functional team environment. Ability to communicate complex technical concepts to non-technical stakeholders. Preferred Skills (Good to Have): Experience with Data Lake architecture and integration. Familiarity with Stream Processing and related technologies. Knowledge of Cloud platforms (AWS, Azure, GCP) and their data services. Experience with Big Data frameworks and data modeling.

Job Overview Senior Engineer - Data Analytics in the Manufacturing domain with 3-7 years of experience. Lead data analytics projects focusing on aerospace reliability and warranty analysis. Develop solutions using Python and Power BI, creating insightful dashboards. Analyze warranty and aftermarket data for valuable insights. Collaborate across teams to address challenges. Streamline data processes using VBA and MS Excel. Drive reliability analysis initiatives for product performance. Communicate findings effectively and mentor junior team members. Demonstrate strong project management and leadership skills. Preferred: Experience in After-market data analysis, strong communication skills, proficiency in VB.Net. Education: Bachelor of Technology or Bachelor of Engineering in Computer Science coupled with an MBA in Business Analytics or Data Science. Preferred certifications: Microsoft Certified: Data Analyst Associate and Certified Reliability Engineer (CRE). Roles & Responsibilities Lead and oversee data analytics projects with a focus on reliability and warranty analysis in the aerospace industry. Utilize Python and Power BI to develop advanced data analytics solutions and create insightful Power BI dashboards for stakeholders. Conduct in-depth analysis of warranty data and aftermarket performance to provide valuable insights and recommendations. Collaborate with cross-functional teams to understand and address the unique challenges of the aerospace aftermarket business. Apply expertise in VBA and MS Excel to streamline data processes and enhance data visualization. Drive reliability analysis initiatives to ensure product performance and customer satisfaction. Communicate findings effectively through reports and presentations. Mentor junior team members and contribute to their professional development. Demonstrate strong leadership skills in project management and team coordination. Maintain a high level of professionalism and uphold ethical standards in data analysis and reporting. Our ideal candidate Extensive experience in Python, Power BI, Warranty Analysis, Aerospace V&V (Verification and Validation) processes, and Reliability Analysis 3-7 years of experience with advanced proficiency in Python for developing data analysis scripts and automation tools Expertise in Power BI for creating interactive visualizations and dashboards In-depth knowledge of Warranty Analysis and Reliability Analysis methodologies Ability to apply VBA and MS Excel for data manipulation and analysis Education: Bachelor of Technology (B.Tech) or Bachelor of Engineering (B.E) in Computer Science or Information Technology, coupled with a Master of Business Administration (MBA) in Business Analytics or Data Science Certification: Microsoft Certified: Data Analyst Associate and Certified Reliability Engineer (CRE) preferred Company overview Altimetrik delivers outcomes for our clients by rapidly enabling digital business & culture and infuse speed and agility into enterprise technology and connected solutions. We are practitioners of end-to-end business and technology transformation. We tap into an organization s technology, people, and assets to fuel fast, meaningful results for global enterprise customers across financial services, payments, retail, automotive, healthcare, manufacturing, and other industries. Founded in 2012 and with offices across the globe, Altimetrik makes industries, leaders and Fortune 500 companies more agile, empowered and successful.Altimetrik helps get companies get unstuck . We re a technology company that lives organizations a process and context to solve problems in unconventional ways. We re a catalyst for organization s talent and technology, helping teams push boundaries and challenge traditional approaches. We make delivery more bold, efficient, collaborative and even more enjoyable. Qualification : Bachelor of Technology (B.Tech) or Bachelor of Engineering (B.E) in Computer Science or Information Technology, coupled with a Master of Business Administration (MBA) in Business Analytics or Data Science

In this role, you will join one of IBM Consulting's Client Innovation Centers (Delivery Centers), where we deliver deep technical expertise and industry insight to both public and private sector clients globally. Our centers provide locally based skills to drive the innovation and adoption of new technologies. A career in IBM Consulting offers long-term relationships and close collaboration with clients worldwide. You ll work alongside visionaries across multiple industries to improve hybrid cloud and AI journeys for some of the world s most innovative and valuable companies. Your ability to accelerate impact and foster meaningful change is enabled by IBM's robust technology platforms, including software and Red Hat. Curiosity and a constant quest for knowledge are key to success, allowing you to challenge the norm, think creatively, and produce groundbreaking solutions for our clients. This environment promotes long-term growth, with ample career development opportunities. Your Role and Responsibilities: As a Big Data Engineer, you will be responsible for the design, maintenance, evaluation, and testing of big data solutions. Your key responsibilities include: Designing, building, optimizing, and supporting data models and ETL processes based on client business requirements. Building, deploying, and managing data infrastructure that can support the needs of a rapidly growing, data-driven organization. Coordinating data access and security to ensure seamless data access for data scientists and analysts when needed. Developing data pipelines/workflows for Source to Target and implementing solutions to address client needs. Ensuring high performance, scalability, and reliability of big data solutions. Required Technical and Professional Expertise: 3-5 years of experience working with Big Data technologies (Hadoop, Spark, HBase, Hive). Proficient in Scala and Python for data engineering tasks, including writing Pyspark programs for data analysis. Good working experience with Python to develop a custom framework for rule generation (similar to a rules engine). Developed Python code to gather data from HBase and implemented solutions using Pyspark. Strong knowledge of Apache Spark, including working with DataFrames and RDDs for business transformations. Experience using Hive Context objects for read/write operations in Hive. Preferred Technical and Professional Expertise: Understanding of DevOps principles and practices. Experience in building scalable end-to-end data ingestion and processing solutions. Familiarity with AWS services (e.g., S3, Athena, DynamoDB, Lambda, Jenkins). Proficiency in object-oriented and/or functional programming languages such as Python, Java, and Scala. As a Big Data Engineer at IBM Consulting, you will have the opportunity to work with cutting-edge technologies, influence industry transformations, and drive meaningful change for a variety of clients. IBM fosters a culture of continuous learning and career development, giving you the resources and support to grow in your role and within the company. This role offers the chance to work on complex, high-impact projects and collaborate with a global team of industry leaders.