Data Engineer (AWS)

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 360,000 team members globally in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms.

• Proven experience in Big Data or Cloud projects involving processing and visualization of large and unstructured datasets across various SDLC phases.
• Hands-on experience with the AWS cloud, including Storage, Compute (and Serverless), Networking, and DevOps services.
• Solid understanding of AWS services, ideally supported by relevant certifications.
• Familiarity with technologies: Glue, Redshift, Lambda, Athena, S3, Snowflake, Docker, Terraform, CloudFormation, Kafka, Airflow, Spark.
• Basic proficiency in at least one of: Python, Scala, Java, or Bash.
• Very good command of English; German language skills are an advantage.

Nice to have:

• Experience with orchestration tools (e.g., Airflow, Prefect).
• Exposure to CI/CD pipelines and DevOps practices.
• Knowledge of streaming technologies (e.g., Kafka, Spark Streaming).
• Experience with Snowflake or Databricks in production or development.
• Relevant certifications in AWS, data engineering, or big data technologies.

• Design and implement solutions for processing large-scale and unstructured datasets (Data Mesh, Data Lake, or Streaming Architectures).
• Develop, optimize, and test modern DWH/Big Data solutions based on the AWS cloud platform within CI/CD environments.
• Improve data processing efficiency and support migrations from on-premises systems to public cloud platforms.
• Collaborate with data architects and analysts to deliver high-quality cloud-based data solutions.
• Ensure data quality, consistency, and performance across AWS services and environments.
• Participate in code reviews and contribute to technical improvements.