Staff Data Engineer

Role Purpose

Build and maintain scalable systems that collect, store, process, and analyse data - including data pipelines, data warehouses, and data lakes - ensuring all data assets remain accurate, accessible, and secure.

As a core member of the engineering team, you will play a key role in building a modern data platform for a growing enterprise. You will take a hands-on approach to both shaping the overarching architecture and delivering initial data products. Working primary with Databricks and AWS, you will design and build production-grade data pipelines, establish engineering standards, and create the reusable patterns, automation, and controls that form the foundation of the platform.

Key Responsibilities & Essential Skills

• Production Databricks & Data Pipeline Engineering: Hands-on experience building production-grade Databricks environments and reliable batch/streaming pipelines using Python, PySpark, and SQL.
• Software Engineering & Automated Delivery: Strong track record in creating modular, maintainable, and reusable components supported by automated pipeline testing, Git-based workflows, and CI/CD deployment.
• Secure Platform Engineering: Experience engineering data systems within secure or regulated environments, including identity and access management (IAM), encryption, secrets management, principle of least privilege, monitoring, and production incident resolution.

Preferred / Highly Valued Experience

• Unity Catalog Expertise: Practical experience configuring data lineage, access permissions, metadata management, and data governance via Unity Catalog.
• Infrastructure as Code (IaC) & Deployment Automation: Hands-on experience with Terraform, Databricks Asset Bundles (DABs), and GitHub Actions or equivalent automated deployment tooling.
• Platform Product & Self-Service Engineering: Experience creating internal developer tools, metadata-driven automation, or paved paths that enable domain teams to build compliant data products independently.