Data Engineer - Pharma R&D
Roche (company site, opens in a new tab)5–8 yrsHyderabadOn-siteDirect career pageEst. 22–38 LPA
Posted 13h ago
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Job description
Structured overview of role & requirements
About This Role
- Build and maintain data ingestion pipelines for diverse unstructured clinical trial data including protocols, ICFs, SmPCs, CSRs, and public clinical databases.
- Design and implement scalable data models in relational (Amazon Aurora) and graph databases to represent and link clinical trial entities and processes.
- Develop and manage ETL workflows, embedding/vectorization pipelines, and APIs to support AI-driven clinical study design and ensure data quality and regulatory traceability.
Minimum Requirements
- Bachelor's degree in Computer Science, Data Engineering, or related field.
- 5-8 years of experience building production-grade data platforms and pipelines.
- Strong proficiency with Python (including PDF/document parsing libraries), advanced PostgreSQL-compatible SQL, and graph databases (Neptune, Neo4j, SPARQL/Cypher).
- Experience with AWS services (Aurora, S3, Lambda, Step Functions), NLP/document processing, pipeline orchestration tools (Airflow, Prefect, etc.), and FastAPI for data serving endpoints.
Ideal Candidate Profile
- Experienced in biomedical knowledge graphs and clinical data domains including PubMed/MEDLINE, ClinicalTrials.gov, and EMA/CTIS data.
- Skilled in designing AI/ML data infrastructure for RAG workflows, embedding/vectorization, and regulatory audit trails in a clinical research environment.
- Comfortable operating in CET timezone with expertise in end-to-end data pipeline development on AWS using CI/CD and Infrastructure as Code.