Data Engineer

Are you a Data Engineer who thrives in a modern Databricks environment and enjoys building scalable, cloud-native data platforms? Do you want to work at the intersection of data engineering, AI enablement and platform architecture in an international organisation?, As a Data Engineer, you play a key role in shaping and scaling the data platform that powers our global Workforce-as-a-Service (WaaS) strategy. You work on our Headless Data Architecture (HDA) a scalable 9-layer, API-first lakehouse architecture built on Azure Databricks, Unity Catalog and Delta Lake.

You are responsible for building reliable, governed and production-ready data pipelines across our global lakehouse ecosystem. From medallion-layer engineering to data contracts and platform observability, you help ensure that data products are scalable, reusable and AI-ready.

Working in a highly collaborative international environment, you contribute directly to the evolution of our global data platform and support advanced analytics, semantic search and AI workloads used across the business.

A key part of your role is combining strong engineering fundamentals with an automation-first mindset. You work with modern AI-assisted development tooling and help build a platform where data engineering, governance and AI capabilities are fully integrated.

You collaborate closely with ML/AI Engineers, Platform Engineers, AI Builders, Cloud Engineers, and stakeholders across regions to continuously improve the platform's scalability, reliability, and quality.

At the same time, you contribute to building a future-proof and governed data ecosystem embedding data quality, lineage, security and compliance standards into every layer of the platform.

What you will do Design, build and maintain Bronze Silver

• Gold medallion pipelines on Azure Databricks
• Develop deployable and version-controlled data products using Lakeflow, Spark Declarative Pipelines and Databricks Asset Bundles (DABs)
• Implement and maintain scalable data contracts and data product patterns across the platform
• Manage and optimise Unity Catalog governance, lineage and access control
• Build and maintain vector and relational storage capabilities supporting AI and semantic search workloads
• Contribute to Databricks Vector Search and AI-enabled retrieval capabilities
• Collaborate with global teams across Europe, the UK, the US and APAC on cross-regional data exchange and platform scalability
• Participate in Git-based development workflows, code reviews and CI/CD practices
• Monitor pipeline health, observability and platform reliability from a DataOps perspective
• Work with AI-assisted development tooling such as Claude Code and the Databricks AI Dev Kit

About the role

You will be part of a growing Global Data & AI Team that is central to the transformation of HeadFirst & Impellam Group into a truly AI-enabled and data-driven organisation.

Working with technologies such as Azure Databricks, Unity Catalog, Delta Lake and Lakeflow, you help build and scale a shared global data platform that supports analytics, AI products and operational intelligence across multiple regions.

This role offers a strong combination of hands-on data engineering, platform ownership and exposure to modern AI-enabled data architectures.

Do you have experience in Unity?, Do you have a Bachelor's degree?, You are a hands-on Data Engineer with a strong technical foundation and a pragmatic mindset for building scalable, governed and production-ready data platforms.

• 3+ years of hands-on experience with Databricks in a production environment
• Strong experience with Medallion Architecture (Bronze / Silver / Gold)
• Solid understanding of Apache Spark and Delta Lake concepts, including optimisation, partitioning and ACID transactions
• Experience with Databricks SQL and Unity Catalog governance
• Familiarity with Lakeflow Connect, Spark Declarative Pipelines and Databricks Asset Bundles (DABs)
• Strong SQL and Python skills for large-scale data engineering workloads
• Experience with Git-based development workflows and CI/CD practices
• Understanding of data contracts, versioning, and scalable data product design.
• Experience with monitoring, observability and DataOps practices
• Familiarity with vector search, semantic search or AI-oriented data workloads is a plus.
• Experience working in a global, multi-lakehouse Databricks setup - ideally hub-and-spoke - with Delta Sharing across regions.
• Familiarity with Azure Synapse Analytics - you will work with Synapse as part of the existing stack while the platform migrates to Databricks-native tooling (Lakeflow, DABs).
• Hands-on experience with SnapLogic - used for integration flows across the organisation outside Databricks, including connectors, pipelines, and the SnapLogic Designer.

What you offer as a professional

• Strong communication skills able to explain technical concepts and trade-offs clearly
• A structured and quality-driven approach to engineering and documentation
• A collaborative mindset, working effectively across global technical and business teams
• A pragmatic approach to building scalable and maintainable data solutions
• Curiosity about AI-native engineering and modern platform development
• A strong drive to continuously learn and contribute to an evolving architecture