AWS Data Engineer

AWS Data Engineer

Job Description Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

We are seeking a skilled AWS Data Engineer to design, build, and optimize scalable data pipelines and architectures on the AWS cloud platform. The ideal candidate will have strong experience in data engineering, cloud technologies, and modern data frameworks to support analytics, reporting, and data-driven decision-making.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using AWS services

• Build and manage data lakes and data warehouses (e.g., Amazon S3, Redshift, Glue)

• Develop and optimize batch and real-time data processing systems

• Ensure data quality, integrity, and governance across systems

• Work with stakeholders to translate business requirements into technical solutions

• Implement data integration solutions across multiple sources and formats

• Monitor and troubleshoot data workflows for performance and reliability

• Optimize costs and performance of AWS data infrastructure

• Collaborate with data scientists, analysts, and DevOps teams

• Required Skills and Qualifications

• Bachelors degree in Computer Science, Engineering, or related field

• 8+ years of experience in data engineering or related roles

• Strong hands-on experience with AWS services, including:

• Amazon S3

• AWS Glue

• Amazon Redshift / RDS

• AWS Lambda

• Kinesis (for streaming use cases)

• Proficiency in SQL and at least one programming language (Python, Scala, or Java)

• Experience with ETL tools and frameworks

• Solid understanding of data modeling, warehousing, and big data concepts

• Familiarity with distributed processing frameworks (Spark, Hadoop)

• Experience with CI/CD pipelines and version control (Git)

• Preferred Qualifications

• Experience with Apache Spark, Kafka, or Databricks

• Knowledge of data governance, security, and compliance

• Familiarity with infrastructure as code (Terraform, CloudFormation)

• AWS certifications (e.g., AWS Certified Data Engineer / Solutions Architect)

• Experience with BI tools (Power BI, Tableau)

• Key Competencies

• Strong problem-solving and analytical skills

• Excellent communication and collaboration abilities

• Attention to detail and commitment to data quality

• Ability to work in a fast-paced, agile environment

• Nice to Have

• Experience with machine learning data pipelines

• Knowledge of real-time analytics and streaming architectures

• Exposure to multi-cloud or hybrid environments