Senior R&D Data Engineer
We are seeking a Senior R&D Data Engineer to design, build, and optimize data capture, processing, and storage solutions that enable advanced analytics and digital process transformation. This role involves creating robust, future‑proof data systems, engineering workflows, and high‑value data repositories that support scientific, technical, and operational decision-making.
Responsibilities
Data Engineering & Pipeline Development
- Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing data from diverse data generation sources and systems (e.g., lab systems, MES, clinical supply, quality systems, external partners).
- Create and optimise data flows for structured and unstructured data using Python (PySpark), R, SQL, Databricks, Snowflake, and other modern engineering tools.
- Develop and maintain specific data repositories, implementing enterprise‑level data models, and creating new models as needed.
- Enable AI/ML readiness by ensuring data is well‑structured, versioned, traceable, and semantically aligned with enterprise data standards.
Data Product & Architecture Partnership
- Partner with data scientists, domain experts, and digital technology teams to translate business needs into high‑quality data products and engineering requirements.
- Work closely with ontology/knowledge graph teams to implement semantic models and future‑proof data architectures.
Quality, Compliance & Performance
- Implement data quality and performance standards; define KPIs to measure accuracy, completeness, and consistency across the data assets.
- Apply data versioning and lineage tracking for compliance, traceability, and audit readiness.
- Follow software development best practices including code versioning, DevOps integration, and documentation.
