• 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. 

Requirements 

•  Extensive experience with Python in a testable and scalable fashion 

• History of successfully developing data pipelines (e.g. Prefect, Airflow, Luigi, Dagster) 

• Hands on experience with RDBMS (Microsoft SQL or PostgreSQL preferred) and comfortable writing SQL, both DDL and DML 

• Experience as lead or managing developer, or substantial experience at senior level. 

• You are able to clearly explain and translate conceptual ideas and technical rationale to technical and non-technical colleagues 

• You have worked as part of teams consisting of 4 or more developers and are used to having your ideas challenged and providing constructive criticism to others 

• Ability to autonomously make architecture and design decisions as lead 

• Demonstrated use of automation and AI-assisted development tools to improve engineering outcomes (quality, speed, test coverage, maintainability) in a controlled and secure way. 

• Experience with DevOps workflows, especially CI/CD 

• Good interpersonal communication and presentation skills 

• Attention to detail 

• Excellent written and verbal English communication skills 

• You are based in Europe, ideally commutable to Amsterdam, Netherlands 

Nice to have 

• Knowledge of medical data standards such as FHIR based data exchange and/or OMOP 

• Exposure to healthcare / life sciences / clinical trials / pharmaceutical data 

• Master Data Management of ideally medical ontologies 

• Data lineage 

• Dutch language skills are a plus for local collaboration and accessing local data sources 

Opportunities 

• You will be a part of innovation in the medical field, contributing to improved outcomes for healthcare patients and providers 

• You will have the opportunity to be responsible for technical communication and preparation in cross-team projects. This will often mean online collaboration with international colleagues. 

• You will collaborate with Machine Learning specialists gaining exposure to ML and Natural Language Processing (NLP) 

• Medical data is an interesting problem space, both in complexity and in societal value. The texts are a domain of its own with extremely high information density. It gives a real kick when users let us know they were able to collect data they were unable to use previously, such as finding people with a rare disease that might take years otherwise to diagnose or rapidly building quality datasets for COVID research 

• You will be part of a larger, cross-functional and dynamic team consisting of developers, designers, medical consultants and ML engineers. 

About us 

• Our Data team currently consists of 1 product owner, 5 developers. 

• The Patient Finder team consists of approximately 30 people organised across three development squads (App, Data, AI/ML), Deployment, Support and Consultancy. 

• Patient Finder team is part of a larger healthcare product portfolio across the EMEA region within the IQVIA business. 

• Our team largely works from home but employees are free to choose between office, home, or hybrid work locations.  Data team typically attend the office weekly. 

• The team is currently location across Amsterdam and Madrid.