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.

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.

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.

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

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)

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. #LI-DNI#EasyApply 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.)

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.

Senior Data Engineer AWS Big Data & API Integration Expert Location: Cochin Experience Required: 5+ years in Data Engineering Job Purpose We are hiring a Senior Data Engineer to lead the development of a scalable and efficient data ingestion framework and ensure high standards of data quality and validation. This role involves designing and implementing robust APIs for seamless data integration and working with modern AWS-based big data technologies. The ideal candidate thrives in complex environments and is passionate about scalable, automated, and high-performance data systems. Key Responsibilities Data Ingestion Framework: Architect, build, and maintain ETL pipelines using services such as AWS Glue, Lambda, EMR, Step Functions, ECS, and EC2. Data Quality & Validation: Implement automated validation checks, monitoring tools, and alerting mechanisms to ensure data accuracy, completeness, and integrity. API Development: Design and develop secure, scalable, and high-performance RESTful APIs with robust documentation and best practices in security, versioning, and performance optimization. Agile Collaboration: Collaborate with stakeholders, analysts, and data scientists to understand business requirements and deliver actionable data solutions. Participate in agile ceremonies and code reviews. DevOps & CI/CD: Contribute to the development of CI/CD pipelines using tools like GitLab, ensuring automated, test-driven deployments. Required Qualifications 5+ years of hands-on experience in data engineering and analytical platform development. Proficient in Python, PySpark, and SQL for large-scale ETL processes. Extensive knowledge of AWS services such as Glue, Lambda, S3, Step Functions, EMR, and ECS. Experience with big data frameworks (e.g., Apache Spark, Apache Iceberg) and databases like DynamoDB, Aurora, PostgreSQL, Redshift. Skilled in building and integrating secure RESTful APIs for internal and external systems. Familiar with CI/CD, automated testing, and agile project management tools. Strong analytical thinking, communication skills, and problem-solving mindset. Preferred Qualifications Bachelor s or Master s degree in Computer Science, Data Engineering, or a related field. Experience with AWS Kinesis, Firehose, SQS, and modern data lakehouse architectures. Prior experience with data quality frameworks and large-scale API-driven data integration in distributed systems. Familiarity with information security standards and adherence to ISMS policies. Qualification : Bachelors or Masters degree in Computer Science, Data Engineering, or a related field.

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.

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 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.

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

Job Description: We are seeking a Data Engineer experience in data and analytics, proficient in big data technologies, data architecture, and customer-focused solutions. The ideal candidate will design and implement data pipelines, data lakes, and visualization solutions to create business value. Software Requirements: AWS Redshift Kubernetes Spark Python SQL DBT Dataiku Overall Responsibilities: Design and implement data pipelines, data lakes, and visualization solutions to create business value. Develop and maintain big data solutions using technologies like AWS Redshift, Kubernetes, Spark, Python, SQL, DBT, and Dataiku. Apply best practices in data architecture, modeling, and metadata management. Analyze and troubleshoot complex data issues, ensuring timely resolution. Collaborate with stakeholders to understand data requirements and deliver customer-focused solutions. Category-wise Technical Skills: Big Data Technologies: Proficiency in AWS Redshift, Kubernetes, Spark, Python, complex SQL, DBT, and Dataiku. Data Architecture & Modeling: Strong understanding of data architecture, modeling, and metadata management. Experience in designing and managing data pipelines and data lakes. Data Analysis & Troubleshooting: Excellent data analytical and troubleshooting skills. Ability to analyze and resolve complex data issues in a timely manner. Experience: 6-8 years of experience in data and analytics. Proven track record of developing and maintaining big data solutions. Day-to-Day Activity: Design, develop, and implement data pipelines and data lakes. Maintain and optimize big data solutions using various technologies. Apply best practices in data architecture and modeling. Analyze and troubleshoot data issues to ensure data integrity and availability. Collaborate with stakeholders to gather requirements and deliver data solutions. Stay updated with emerging trends in data and analytics. Qualifications: Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field. Relevant certifications in big data technologies and data engineering are a plus. Soft Skills: Strong analytical and problem-solving skills. Excellent communication and collaboration skills. Customer-focused approach with the ability to understand and meet stakeholder needs. Attention to detail and strong organizational skills. Ability to work independently and as part of a team. S YNECHRON S DIVERSITY & INCLUSION STATEMENT Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. Qualification : Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.

Job Title: Data Engineer Location: Rajkot, Gujarat, India Company: IBM Consulting Introduction A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for some of the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio, including Software and Red Hat. At IBM, curiosity and a constant quest for knowledge serve as the foundation for success. You'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions that make groundbreaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experiences. In this role, you ll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients. Our delivery centers provide locally based skills and technical expertise to drive innovation and adoption of new technologies. Your Role and Responsibilities As a Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in developing data solutions using Spark Framework with Python or Scala on Hadoop and AWS Cloud Data Platform. Key Responsibilities: Data Pipeline Development: Build data pipelines to ingest, process, and transform data from files, streams, and databases. Process the data using Spark, Python, PySpark, Scala, and Hive, HBase, or other NoSQL databases on Cloud Data Platforms (AWS) or HDFS. Software Code Development: Develop efficient software code for multiple use cases leveraging Spark Framework, using Python or Scala and Big Data technologies for various use cases built on the platform. Streaming Pipelines: Develop streaming pipelines to process real-time data. Cloud Data Solutions: Work with Hadoop/ AWS ecosystem components to implement scalable solutions to meet the increasing data volumes using big data/cloud technologies like Apache Spark, Kafka, etc. Big Data/Cloud Technologies: Build scalable solutions on AWS, including tools like AWS EMR, AWS Glue, DataBricks, AWS Redshift, DynamoDB, and other cloud technologies. Required Education Bachelor's Degree in Computer Science, Engineering, or a related field. Required Technical and Professional Expertise 5 - 7+ years of experience in Data Management (DW, DL, Data Platform, Lakehouse) and Data Engineering skills. Minimum 4+ years of experience in Big Data technologies with extensive experience in Spark, Python, or Scala. Minimum 3 years of experience on Cloud Data Platforms (preferably AWS). Exposure to streaming solutions and message brokers like Kafka technologies. Proficiency in SQL. Experience with AWS EMR, AWS Glue, DataBricks, AWS Redshift, DynamoDB. Preferred Technical and Professional Experience Certification in AWS, Data Bricks, or Cloudera Spark Certified Developers. About IBM Consulting IBM Consulting is IBM s consulting and global professional services business, with market-leading capabilities in business and technology transformation. With deep expertise in many industries, we offer strategy, experience, technology, and operations services to many of the most innovative and valuable companies in the world. Our people are focused on accelerating our clients businesses through the power of collaboration. We believe in the power of technology responsibly used to help people, partners, and the planet. Qualification : Bachelor's Degree in Computer Science, Engineering, or a related field.q

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)

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.

Software Development Manager Experience: 8+ Years Location: Bangalore Company: Kaleidofin About Us Kaleidofin is a mission-driven fintech platform committed to delivering financial solutions for underserved communities. Our proprietary ki credit platform combines advanced credit health analytics, middleware integration, risk dashboards, and debt capital structuring empowering financial institutions to serve low-income customers, informal sector businesses, and MSMEs more effectively. Operating across India, Bangladesh, and Kenya, we ve already impacted over 6 million customers, enabling over $3 billion in debt capital for underserved communities. Backed by global investors including the Gates Foundation, Omidyar Network, and Blume Ventures, Kaleidofin is recognized as a leader in inclusive finance. Featured on Forbes Asia's "100 to Watch" Winner of RBI s Swanari TechSprint 2023 Winner of G20 TechSprint 2024 by BIS Certified as a Great Place to Work Role Overview As a Software Development Manager, you will play a key leadership role in shaping the technical roadmap and executing high-impact fintech products. You ll lead a team of engineers to build scalable, secure, and robust systems. This is a hands-on leadership role requiring active involvement in design, architecture, and code-level decisions. What You ll Do Own the product s engineering roadmap, architecture, scalability, and code quality. Guide system design decisions and lead architecture/code reviews. Collaborate closely with Product and Business teams to align on product strategy and feature development. Provide hands-on technical leadership especially in solving complex problems in fintech and lending domains. Mentor and develop engineering talent; foster a culture of ownership, innovation, and quality. Champion engineering best practices including test automation, CI/CD, and DevOps. Lead the adoption of data-driven practices including Big Data, PySpark, and data pipeline architectures. Balance short-term deliverables with long-term technical sustainability and scalability. Support team growth through career development, learning plans, and succession planning. 8+ years of software development experience, with 1 2+ years in people/team management roles. Strong fundamentals in computer science, system design, and problem-solving. Bachelor's or Master's degree in CS or related field from a top engineering institution (IITs, NITs, etc.). Proven experience building distributed, scalable, and secure systems. Strong hands-on experience with Python, Java, Spring Boot, and microservice architectures. Proficient in SQL/NoSQL, Kafka, CI/CD pipelines, and DevOps tools (Docker, Kubernetes, Jenkins, etc.). Familiarity with AI/ML model integration and credit scoring systems is a strong plus. Experience with data engineering: Big Data, Spark, Airflow, AWS stack (S3, Glue, Athena), etc. Knowledge of front-end and mobile (Android) development is a plus. Experience working in fintech, lending tech, or high-growth startup environments preferred. Excellent leadership, communication, and cross-functional collaboration skills. Be part of a high-impact team driving financial inclusion at scale. Work on cutting-edge technology in fintech and data infrastructure. Grow with a company that s winning global recognition and delivering real-world impact. Contribute to a people-first culture that values learning, innovation, and work-life balance. Qualification : Bachelor's or Master's degree in CS or related field from a top engineering institution

Data Scientist Experience: 5+ Years Location: Bangalore, Karnataka, India Job Type: Full Time Job Summary We are seeking an experienced Data Scientist with over 5 years of expertise to join our innovative team in Bangalore. The ideal candidate will have hands-on experience in advanced statistical methods, machine learning, and deep learning frameworks, combined with strong skills in deploying models at scale. Key Responsibilities Apply advanced Statistics and Operations Research methods to solve complex business problems. Develop and deploy predictive and machine learning models using frameworks such as PyTorch, TensorFlow, Keras, and XGBoost. Utilize data engineering and big data tools including PySpark, Databricks, and Flask for building scalable data solutions. Implement and fine-tune NLP models like RNN, LSTM, and attention-based architectures, leveraging pre-trained models from Stanford, IBM, Azure, and OpenAI. Design and optimize efficient SQL queries to extract data from large databases. Work with visualization tools like D3.js, Dash Plotly, and deploy interactive dashboards using Streamlit. Utilize graph databases such as Neo4j for complex data relationships. Manage version control with tools like GitHub or Bitbucket. Deploy machine learning models into production environments using MLOps practices on cloud platforms such as AWS or Azure. Required Skills 5+ years of professional experience as a Data Scientist or similar role. Strong foundation in statistics, machine learning, and deep learning techniques. Proficient in Python-based data science libraries and frameworks. Hands-on experience with cloud-based MLOps and deployment. Excellent SQL skills for data extraction and manipulation. Experience with version control systems and collaborative development. Familiarity with NLP techniques and modern pre-trained language models. Strong problem-solving and communication skills. Qualifications Any graduate degree in Computer Science, Statistics, Mathematics, Engineering, or related field. Join a forward-thinking company in Bangalore, where you will work with cutting-edge technologies to create impactful data-driven solutions. Grow your career in an environment that values innovation, diversity, and continuous learning.