We’re looking for a Senior Data Engineer to join Apadmi and establish a high-performing data engineering capability for one of our key strategic healthcare accounts. In this senior, hands-on role, you will provide technical leadership across a specialist team of engineers working with cloud-based data infrastructure, business intelligence tooling, and client-facing analytics products. This is the perfect opportunity for someone technically deep who has the patience, credibility, and leadership skills to embed modern engineering discipline into a growing data function. You will sit at the intersection of technology delivery and data engineering, owning the data platform roadmap and governing the quality of all data outputs. Operating as an agile team leader, you will collaborate closely with operational, clinical, and commercial stakeholders to ensure the delivery of trusted, scalable, and beautifully documented data products. You'll be responsible for bringing software engineering rigour to a team expanding its technical maturity, establishing the right ways of working from the outset. As a Senior Data Engineer, you will define and own the data platform architecture while establishing team-wide standards across source control, environment management, peer reviews, and release processes. You will blend high-level strategy with hands-on automation, ensuring data quality checks are built-in from day one. Additionally, you will guide your squad through Agile sprint ceremonies and line-manage engineers to foster a culture of quality. What you'll be working on - Define and own the technical architecture of the cloud data platform, ingestion pipelines, and semantic reporting layer. - Establish and enforce core engineering standards, including Git-based source control, branching strategies, environment management, and peer code reviews. - Design scalable, maintainable data models and pipeline architectures that shift the function from reactive data handling to reusable data products. - Line-manage and mentor a team of three engineers, supporting their professional development in modern engineering discipline through collaborative working. - Drive the adoption of Agile methodologies, including sprint planning, stand-ups, retrospectives, and structured backlog refinement. - Proactively automate recurring workflows, forecasting processes, and ingestion monitoring to reduce manual effort and increase reliability. - Embed strict data quality checks at the point of ingestion and establish data dictionaries to secure strict metric governance before data reaches external audiences. - Translate complex business requirements into deliverable user stories, providing accurate effort estimates and managing technical dependencies. What you’ll bring to the team You are a solution-driven data leader who has spent time working within or alongside structured software development teams. You understand the rigour of technology delivery functions and possess a low tolerance for ambiguous data definitions. You are highly collaborative, capable of managing complex roadmaps, and excel at translating technical trade-offs into clear insights for non-technical stakeholders. - Proven experience in a senior data engineering or tech lead role with direct line management responsibility. - Strong hands-on experience with cloud data platforms, ideally utilizing Azure Data Factory, Azure SQL, or Synapse Analytics. - Demonstrable experience implementing CI/CD pipelines, automated testing, environment management, and Git practices within a data team. - Deep understanding of fact/dimension design, semantic layers, and advanced BI tool development (ideally Power BI and DAX). - Solid coding or scripting experience (ideally Python) used to automate data workflows and solve complex pipeline challenges. - Track record of introducing and sustaining agile delivery practices, backlog management, and iterative delivery metrics. - Exceptional communication skills to engage credibly with senior operational, clinical, and commercial business leaders. - Experience establishing data functions from a low baseline, familiarity with dbt, or experience working within highly regulated data environments like healthcare would be beneficial.