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.
