Senior Data Engineer

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.

Role Overview:

As a
Data Engineer
in our team, you will

• Ensure stable, compliant, and cost-optimized data flows from the tool to the Cloud Data Hub (AWS Environment).
• Maintain and enhance analytics-ready datasets powering Palantir Foundry applications (KRI Report, LOPA Tool, ESPRO Dashboard) and ad hoc reporting.
• Support future-proofing of the platform, including potential pipeline migration (e.g., Azure to AWS).

Responsibilities

• Own end-to-end data architecture for tool-to-CDH flows; set standards for data modeling, orchestration, testing, observability, and cost governance.
• Plan and execute platform transitions (e.g., Azure to AWS for CDH), establishing monitoring and high-stability operations in the new environment.
• Coordinate with software developers, BI/analytics stakeholders, and compliance to align backlog, prioritize user requests, and de-risk changes.
• Mentor the Data Engineer; review code, enforce quality gates, and drive continuous improvement.

Your Role

• Operate and maintain the existing Azure pipeline integrating the tool data into the group's AWS environment; monitor uptime, performance, and costs; minimize downtime.
• Build, optimize, and document ETL/ELT processes for data ingestion, transformation, and transparency of data updates.
• Maintain connections and data contracts with upstream/downstream systems; perform failure analysis across interfaces and redeploy fixes in integration environments.
• Maintain and evolve analytics datasets supporting Palantir Foundry apps; deliver prioritized ad hoc reports on the tool and related logistics data.
• Ensure GDPR-aligned handling of personal data and adherence to the group's compliance (eGRC, connectIT), with documentation and audit readiness in Confluence.
• Keep documentation and code updated after each change; contribute to sprint planning, demos, and retrospectives in the group's agile framework.

Your Profile

• 5 to 9 years of Data Engineering experience
• Bachelor's degree in computer science, software engineering, information technology, or a related field.
• Strong experience in cloud data engineering with
  AWS-based pipelines
  and services used for data movement and orchestration.
• Practical knowledge of integrating with enterprise Cloud environments.
• Proficiency in
  Python, Pyspark, AWS Glue
  ; experience with
  ETL/ELT patterns
  and performance tuning.
• Experience with
  PostgreSQL
  and working with microservice-produced data.
• Proven track record in production monitoring, alerting, incident management, and change/release practices.
• Familiarity with
  GDPR
  and enterprise compliance; ability to maintain audit-ready documentation.

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, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.