Role: Data Engineer
Remote / Onsite: Onsite
Experience: 8+ Years
Role summary
You will combine clinical data expertise with strong data engineering and technical skills to generate well documented pipelines from source to curated data sets in common data models like CDISC SDTM. You will collaborate closely with clinical SMEs, data scientists, infrastructure, and other skilled data engineers.
We are looking to expand this functionality to include Real World Data (from a broad range of regristries). You will help extend our medallion Databricks pipelines (CDISC SDTM) to incorporate Real World Data (RWD) from registries and other sources, working with clinical experts and AI teams to combine rule based and automated mapping approaches (including OMOP interoperability).
Key responsibilities
- Design, build and maintain production ETL pipelines in Databricks/Delta Lake to ingest RWD (registries, claims, EHR extracts) and transform into standard models.
- Implement harmonisation workflows to map incoming RWD to OMOP and to the internal CDISC SDTM canonical model; handle vocabulary mapping, units normalization and provenance.
- Extend the medallion architecture (bronze/silver/gold) patterns with robust validation, lineage, partitioning and performance tuning.
- Develop configurable, inputdriven transformation frameworks so clinical experts can drive mapping rules via config files and catalogs.
- Integrate AI/automation components (e.g., model-assisted mapping, NLP for free text) with humanintheloop review and confidence scoring.
- Establish testing, CI/CD, monitoring and alerting for ETL jobs and automations; ensure reproducibility, versioning and governance.
- Collaborate with clinical data scientists, data stewards and stakeholders to define requirements, data contracts and success metrics.
Required skills and qualifications
- Proven experience designing and implementing ETL pipelines in Databricks / Spark and Delta Lake.
- Strong knowledge of OMOP CDM and experience mapping datasets to OMOP; familiarity with CDISC SDTM is a plus.
- Expertise in data modelling, partitioning, performance tuning, and best practices for large clinical/RWD datasets.
- Experience with vocabulary services and terminology mapping (OHDSI/Athena, UMLS, or similar).
- Experience integrating AI/NLP components into data pipelines (entity extraction, mapping suggestions) is desirable.
- Familiarity with testing frameworks for data (Great Expectations, Deequ), CI/CD, infrastructure as code, and orchestration tools (Databricks Jobs, Airflow).
- Good communication skills and experience working with domain experts to capture requirements. Preferred
- Prior experience in pharma or clinical research environments.
- Knowledge of data governance, privacy regulations and secure handling of patient data.
- Experience with Unity Catalog, Databricks Delta Sharing, and cloud infrastructure (Azure/AWS).
Pay: ₹80,000.00 - ₹100,000.00 per month
Work Location: In person
