Senior Data Engineer

Performance Team | Brighton / mostly remote

We’re looking for a Senior Data Engineer to join Apadmi and help establish and drive high-impact data engineering capabilities for one of our key healthcare client accounts. This is a senior, hands-on role combining technical depth with team leadership to build cloud-based data infrastructure, business intelligence tooling, and client-facing analytics products. If you bring strong software engineering disciplines to data platforms and enjoy mentoring teams to raise technical capability, this is the role for you.

Working closely with operational, clinical, and commercial stakeholders, you will own the technical data platform roadmap and govern the quality of all data outputs. Operating within an Agile environment, you will bridge the gap between software delivery best practices and data engineering, embedding modern ways of working while line-managing a specialist team of engineers to deliver trusted, scalable, and well-documented data products.

What you’ll be working on

• Take ownership of the end-to-end data platform, from API ingestion through to curated datasets and governed reporting outputs.
• Act as the technical authority across data engineering, analytics engineering, and BI development disciplines, establishing engineering standards such as Git workflows, CI/CD, and peer reviews to transition the team toward reusable, well-modeled data products.
• Define and own the technical architecture of the data platform, cloud data warehouse, ingestion pipelines, and semantic reporting layers.
• Establish engineering best practices across the team, including Git source control, branching strategies, environment management (dev/test/prod), and automated testing.
• Line manage and mentor a team of three engineers, fostering professional growth and embedding quality-first engineering principles through collaborative working.
• Oversee data ingestion pipelines, ensuring reliable monitoring, error handling, and quality checks at the point of ingestion rather than retrospectively.
• Lead Agile delivery ceremonies (stand-ups, sprint planning, retrospectives) and manage the team backlog, breaking complex requirements into refined user stories.
• Drive process automation across data production, reporting, and forecasting workflows using pragmatic scripting to eliminate manual tasks.
• Maintain strict data governance, establishing formal QA sign-off processes, versioned data dictionaries, and escalation workflows before data reaches client audiences.
• Engage with senior operational, clinical, and commercial stakeholders to translate complex business needs into clear technical roadmaps and data products.