Hybrid Senior Data & AI Platform Engineer

Capgemini Engineering

Fundão

Hybrid

EUR 90,000 - 120,000

Full time

40 hours ago
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Benefits offered by this job

Hybrid work
Health and life insurance
Referral program

Job summary

Capgemini Engineering seeks an experienced Senior Data Platform Engineer to define, implement, and govern data and AI platforms across Azure-based ecosystems. You will guide engineering teams, ensure enterprise alignment, and drive platform modernization initiatives.

Ideal candidates have extensive experience with Azure Databricks, Microsoft Fabric, Purview, and Power BI, and possess strong governance, CI/CD, and DevOps skills.

Qualifications

  • 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 design, development, and operation of scalable, production-ready data solutions.
  • Ensure alignment with Architecture, Security, Governance, and FinOps principles.
  • Drive 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.

Skills

Data engineering
Cloud engineering
Data & AI platforms
Azure Databricks
Microsoft Fabric
Microsoft Purview
Power BI
Terraform
GitHub Actions

Tools

Azure Databricks
Microsoft Fabric
Microsoft Purview
Unity Catalog
Power BI

Job description

Capgemini Engineering seeks an experienced Senior Data Platform Engineer to define, implement, and govern data and AI platforms across Azure-based ecosystems. You will guide engineering teams, ensure enterprise alignment, and drive platform modernization initiatives.

Ideal candidates have extensive experience with Azure Databricks, Microsoft Fabric, Purview, and Power BI, and possess strong governance, CI/CD, and DevOps skills.

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