Senior Data & AI Platform Engineer (Hybrid)

Capgemini Engineering; Lisboa; Hybrid; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Hybrid work

Health and life insurance

Referral program with bonuses

Great office locations

Job summary

Capgemini Engineering in Lisbon seeks a seasoned Data & AI Platform Architect to define, implement and govern enterprise data solutions. You will lead cross‑functional squads, align with security and governance, and push cloud modernization across Azure, Databricks and Fabric.

The role combines hands‑on engineering with strategic platform thinking, fostering cost optimization and scalable data products, with hybrid work in Portugal.

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

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.

Skills

Data Engineering

Cloud Engineering

Data & AI Platforms

Tools

Azure

Azure Databricks

Microsoft Fabric

Power BI

Microsoft Purview

Unity Catalog

Terraform

Job description

Capgemini Engineering in Lisbon seeks a seasoned Data & AI Platform Architect to define, implement and govern enterprise data solutions. You will lead cross‑functional squads, align with security and governance, and push cloud modernization across Azure, Databricks and Fabric.

The role combines hands‑on engineering with strategic platform thinking, fostering cost optimization and scalable data products, with hybrid work in Portugal.