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Capgemini

Global consulting, technology services, outsourcing

Data & AI Senior Engineer

Data ManagementUpdated on Nov 14
Full-timeNo salary listed

About the Job

Requirements

  • At least 10 years of experience in Data Engineering, Cloud Engineering, or Data & AI Platforms.
  • Strong technical expertise in designing and implementing enterprise-scale data platforms and architectures.
  • Proven experience with Microsoft Azure and modern Data & AI ecosystems.
  • Hands-on experience with Azure Databricks, Microsoft Fabric, Microsoft Purview, Unity Catalog, and Power BI.
  • Strong understanding of Data Lake, Lakehouse, and modern analytics architectures.
  • Experience designing and implementing scalable data pipelines and data products.
  • Solid knowledge of data governance, metadata management, lineage, data quality, and access control frameworks.
  • Experience with DevOps and DataOps practices, including CI/CD, GitHub Actions, and Infrastructure as Code (Terraform).
  • Strong understanding of environment lifecycle management across Development, Pre-Production, and Production environments.
  • Experience defining standards for workspace management, monitoring, observability, and platform operations.
  • Knowledge of FinOps principles, cloud cost optimization, and workload management.
  • Experience supporting cloud migration and modernization initiatives.
  • Strong stakeholder management, communication, and collaboration skills.
  • Ability to balance hands-on technical work with governance and strategic platform thinking.

Responsibilities

  • Define, implement, and maintain engineering standards, frameworks, and best practices across Data & AI platforms.
  • Support and guide engineering teams in the design, development, and operation of scalable and production-ready data solutions.
  • Ensure alignment with enterprise Architecture, Security, Governance, and FinOps principles.
  • Drive the adoption of modern Data & AI platform capabilities across Azure, Databricks, Microsoft Fabric, and related technologies.
  • Establish and govern platform standards for data pipelines, data products, semantic models, access management, and lineage.
  • Define and promote best practices for CI/CD, Infrastructure as Code, environment management, and platform operations.
  • Collaborate with Architecture, Security, Governance, and delivery teams to ensure compliance with enterprise standards.
  • Support platform modernization initiatives, including migration from legacy solutions to cloud-native architectures.
  • Define standards for workspace organization, monitoring, observability, and operational excellence.
  • Promote cost optimization and resource efficiency through FinOps practices and compute optimization strategies.
  • Enable engineering teams through technical mentorship, guidance, and continuous improvement initiatives.
  • Contribute to the evolution of the organization's Data & AI platform strategy and operating model.

Desired Qualifications

  • Microsoft Azure, Fabric, Databricks, or related certifications are considered a plus.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

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