Data Engineer

About the role

We are seeking an experienced Data Engineerto build the foundational data infrastructure supporting a large-scale clinical trial operational and financial forecasting programme. You will design and deliver reliable, scalable data products that enable forecasting across the full trial lifecycle, including study, site, subject, visit and procedure-level activity. Your work will underpin downstream analysis of investigator fees, laboratory kits, resource demand and revenue recognition.

This is a hands-on engineering role operating across complex clinical trial data domains. You will work with contract, budget, operational and actuals data from multiple enterprise source systems, ensuring that data is integrated, reconciled and available at the right level of granularity. You will build solutions that support multi-currency, multi-site and multi-country studies, while maintaining the governance, traceability and version control required for trusted forecasting outputs.

Key responsibilities

• Develop automated ingestion pipelines for contract and budget data, together with structured consumption layers that make trusted data available to forecasting products and business users;

• Integrate site-level rate and budget data, build feedback pipelines that return operational actuals at forecast grain, and publish versioned datasets for use by several forecasting initiatives;

• Define and implement a common data ontology and knowledge graph, establishing consistent identifiers and relationships across upstream and downstream systems;

• Create and maintain a governed source-of-truth register with clear versioning and amendment tracking.

• Partner with stakeholders to ensure the subject-level visit projection engine—the primary downstream consumer—receives accurate, timely and well-documented data;

MUST-HAVE SKILLS

Data Pipeline Development and Data Product Delivery:

• Strong, hands-on experience designing, building and maintaining robust production data pipelines. You can automate ingestion, transformation and publication of data from multiple source systems, and you understand how to produce reusable, versioned datasets that meet the needs of several downstream products;

• Experience working with data at different operational grains and delivering reliable data products in a governed enterprise environment is essential;

Enterprise Data Integration:

• Integrate complex datasets from operational, contractual and financial systems, resolving differences in data models, identifiers and business definitions. You are comfortable building a shared integration layer that supports data across countries, sites and currencies, while preserving the detail required at study, site, subject, visit and procedure level;

Data Ontology, Knowledge Graphs and Master Data:

• Practical experience in designing data ontologies, canonical models or knowledge graphs that create consistent entities, identifiers and relationships across disparate systems. You understand how this capability supports data reconciliation, lineage and trusted cross-domain analytics. You can apply these principles to establish a governed source of truth with clear version control and amendment history;

Clinical Trial, Life Sciences or Complex Operational Data

• Experience working with complex operational data, ideally within clinical trials, life sciences or a similarly regulated environment. You understand the importance of data quality, auditability and traceability where data informs operational and financial decision-making;

• Exposure to clinical trial contracts, budgets, site data, subject activity or visit-level data will be particularly valuable;

NICE TO HAVE

• Experience supporting forecasting, planning or revenue-recognition data products — useful for understanding the needs of the programme’s downstream consumers.

• Experience with actuals-versus-forecast feedback loops — valuable for improving forecast accuracy and operational learning over time.

• Familiarity with subject-level visit projection or patient journey models — beneficial for supporting the programme’s principal forecasting engine.

• Experience operating in multi-country, multi-currency environments — useful when designing scalable and consistent data solutions across global trials.