We're looking for an experienced Data Platform Engineer to help improve and scale a governed, compliant, and cost-effective Azure lakehouse platform and managed Databricks environment.

About the platform

The Data Analytics Platform provides reusable components for data extraction, ingestion, harmonization, and quality. It enables business units to build analytics platforms and data products faster, with reduced cognitive load.

The managed Databricks environment offers non-IT users a simplified experience with built-in governance and automation to support data-driven experimentation and insight generation.

🎯 Responsibilities

• Refine, build, test, deploy, and automate core data components for the platform and Data Lab.
• Deliver reusable, standardised components through a common codebase for internal customers.
• Understand the needs of different business units and translate them into modular solutions that can serve a broad range of users.
• Brainstorm and design platform architecture improvements with other team members.
• Contribute to the product vision, team learning, and technical discussions.
• Mentor colleagues and support the development of less experienced engineers.
• Share knowledge across the data engineering community and collaborate through pair programming and code reviews.
• Lead, guide, or participate in the platform’s inner-source community.
• Enable business teams to deliver successful data and AI projects.

🛠️ Technologies

• Microsoft Azure cloud infrastructure
• Infrastructure as Code
• Azure Data Factory (ADF) for pipelines and orchestration
• Databricks for data processing and transformation
• Python, including PySpark
• SQL
• CI/CD, packaging, and testing
• Bicep and, as a plus, Pulumi

🛠️ Requirements

• 5–7+ years of relevant experience in software, data, and/or platform engineering.
• Experience building modular, testable, scalable, and easily consumable platforms.
• Significant experience with Azure data and platform engineering, including ADLS, Delta Lake, Databricks, and ADF.
• Proven experience delivering multi-tenant or productised data platforms.
• Strong software engineering fundamentals, including Python, PySpark, SQL, CI/CD, packaging, testing, and Infrastructure as Code.
• Practical expertise in lakehouse and medallion architecture.
• Experience with data quality, lineage and metadata, and cloud cost and performance optimisation.
• Awareness of security and governance in regulated environments, including Unity Catalog, role- or attribute-based access, secrets, and policies.

➕ Nice to have

• Experience with platform-level monitoring, observability, and lifecycle management.
• Familiarity with event-driven patterns and streaming.
• Exposure to LakeFlow and its evolution alongside Azure Data Factory.
• Experience preparing platforms for API-driven data product exposure and higher-availability patterns.
• Participation in data engineering communities or guilds.

🤝 Team and ways of working

• Collaborate with a diverse, international team of data and cloud platform engineers.
• Work in an agile environment with two-week sprints.
• Focus on customer needs while contributing across both data engineering and cloud infrastructure.
• Help the team determine the best technical approach with a high degree of autonomy.
• Deliver value with a quality-first mindset.

🤗 Benefits

• Starting financial support to equip your home workspace.
• Allowances and telework subsidies.
• Flexible working hours and two months of intensive summer working hours.
• Life insurance and a pension plan.
• Performance-related bonus.
• Free parking for cars, motorbikes, electric cars with chargers, and bicycles.
• Flexible compensation options, including a transport card, nursery vouchers, health insurance, and training.
• Volunteer opportunities and time dedicated to community activities.
• Wellness programme.

Please submit your CV in English.