Capgemini
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Chennai · On-site · 6-9 Yrs · Nov 2
Enterprise Software & Network Solutions · 10000+ Employees · Paris, France
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of €22.5 billion. Capgemini in India comprises nearly 175,000 team members working across 13 locations: Bangalore, Bhubaneswar, Chennai, Coimbatore, Gandhinagar, Gurugram, Hyderabad, Kolkata, Mumbai, Noida, Pune, Salem and Tiruchirappalli. Get The Future You Want | Learn more about Capgemini in India at www.capgemini.com/in-en.
Hiring: Engineering, Marketing, Human resources
What employees say
+ Good company to begin your career as a fresher and retire as an experienced professional
− Not a good org in the middle band, as limited career growth opportunities and pay hike is minimal as compared to market standards
More reviews on the company profile.
Interview experience · Senior Consultant
I attended a walk in interview drive. The arrangement was good and the panel was knowledgeable. The questions were moderately difficult and there was two technical rounds, followed by a HR round.
Average difficulty · India · 17,487 reports
More interview insightsJob description
Overview
Join a team focused on building large-scale data platforms and analytics solutions. As a Data Engineer, you will design, develop, and optimize high-volume data pipelines leveraging AWS cloud services, PySpark, and modern data lake architectures.
Responsibilities
- You will be responsible for developing and maintaining scalable data pipelines, processing large datasets, and enabling reliable data solutions for business analytics and operational reporting. The role involves working with AWS services, ETL/ELT frameworks, orchestration tools, and data lake technologies.
- Design, develop, and maintain scalable data pipelines to process data from multiple enterprise platforms.
- Build, manage, and optimize large-scale ETL/ELT workflows handling high-volume data workloads.
- Develop data processing applications using PySpark, Spark SQL, and Python on AWS EMR.
- Create and optimize Athena (Trino/Presto) queries for reporting, troubleshooting, and data analysis.
- Design, implement, and enhance data lake solutions using Amazon S3, AWS Glue, Athena, and EMR.
- Collaborate with business analysts, data scientists, and stakeholders to deliver reliable and scalable data solutions.
- Support migration and modernization initiatives involving Airflow/MWAA and workflow orchestration platforms.
- Implement data validation, monitoring, and quality checks to ensure data accuracy and consistency.
- Troubleshoot production pipeline failures, performance bottlenecks, and data quality issues.
- Follow DevOps and CI/CD best practices using GitLab for code management and deployments.
- Participate in architecture discussions, code reviews, and technical design activities.
- Create technical documentation, test plans, and operational runbooks.
Qualifications
- 6–12 years of experience in Data Engineering and Big Data technologies.
- Strong hands-on experience with Python, PySpark, and Spark SQL.
- Expertise in AWS EMR, Amazon S3, AWS Glue, and Athena.
- Experience building and maintaining large-scale ETL/ELT pipelines.
- Strong knowledge of data lake architectures and data warehousing concepts.
- Experience with workflow orchestration tools such as Airflow/MWAA.
- Strong SQL skills and experience with Trino/Presto/Athena query optimization.
- Experience with data validation, monitoring, and troubleshooting.
- Familiarity with GitLab, CI/CD pipelines, and DevOps practices.
- Strong analytical and problem-solving capabilities.
Nice to have
- Experience with telecom, network, billing, provisioning, or large enterprise datasets.
- Knowledge of real-time and batch data processing frameworks.
- Exposure to data governance and data quality frameworks.
- Experience with cloud-native analytics and reporting solutions.
- Understanding of Agile development methodologies.
- What You'll Love About Working Here
- Work on large-scale cloud and big data platforms.
- Exposure to modern AWS data engineering technologies.
- Opportunity to solve complex data processing and analytics challenges.
- Collaborative environment with data scientists, engineers, and business teams.
- Continuous learning and career growth in cloud and data engineering.
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Job application FAQ
Last updated 6 November 2026
- How do I apply for Data Engineer – AWS Big Data & PySpark at Capgemini?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Capgemini may attach structured assessments to interview rounds after you apply.
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- Is Data Engineer – AWS Big Data & PySpark remote or on-site in Chennai, Tamil Nadu?
- This listing is marked on_site with location Chennai, Tamil Nadu. Confirm details on the job description before applying.
- What skills matter for this Data Engineer – AWS Big Data & PySpark role at Capgemini?
- This is a mid-level Data Engineer – AWS Big Data & PySpark role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.