
Lead Data Engineer
IQVIA
Lead Data Engineer
Lead Data Engineer needed for IQVIA's Patient Finder product, a healthcare search engine used by 40+ hospitals in the Netherlands and Belgium. The role involves driving the technical direction of data pipeline and warehouse layers, mentoring a team, and collaborating with product and engineering stakeholders. Requires extensive Python, data pipeline, and SQL experience, with a preference for healthcare data knowledge.
Lead Data Engineer
Lead Data Engineer needed for IQVIA's Patient Finder product, a healthcare search engine used by 40+ hospitals in the Netherlands and Belgium. The role involves driving the technical direction of data pipeline and warehouse layers, mentoring a team, and collaborating with product and engineering stakeholders. Requires extensive Python, data pipeline, and SQL experience, with a preference for healthcare data knowledge.
Salary
Core Qualifications
Technical (Must-have)
Soft Skills
Preferred Qualifications
Technical (Nice-to-have)
Tools (Nice-to-have)
Key Responsibilities
- Lead end-to-end design and delivery of the data platform (pipelines + warehouse layers), primarily using Prefect, Python and SQL, supported by fit-for-purpose design artefacts and lineage.
- Drive platform evolution by standardising patterns, reducing operational overhead, and improving maintainability and reliability across the data landscape.
- Ensure continuity and quality during change via release planning, validation strategies, risk management, and clear technical stakeholder communication.
- Partner with Product and Engineering to refine requirements, shape delivery plans, and prioritise backlog/work intake based on value, dependencies, and technical constraints.
- Raise engineering standards through reviews, quality practices, and responsible AI-assisted engineering (e.g., accelerating development and strengthening tests/refactoring under clear controls).
- Collaborate with QA to increase test maturity, coverage, and automation for pipelines and data transformations.
- Collaborate with Application and AI/ML leads to integrate data components with the wider product ecosystem (e.g., search and ML pipelines).
- Lead the data engineering team (line management where applicable), coaching engineers and owning work intake and prioritisation.