Clinical Data Engineer, OMOP

Job description

A leading organization is seeking a Clinical Data Engineer to onboard new clinical data sources into a standardized analytics environment using the OMOP Common Data Model. The position focuses on source-to-OMOP mapping, data pipeline development, clinical terminology standardization, patient identity validation, and data quality.

The engineer will work across multiple source-enablement efforts, transforming clinical data into standardized, analytics-ready OMOP tables using SQL, BigQuery, Airflow, and GCP technologies.

Responsibilities

• Design source-to-OMOP mappings that translate incoming clinical data into appropriate OMOP domains and tables.
• Develop and maintain SQL transformations and Airflow DAGs for clinical data ingestion, transformation, and loading.
• Validate patient identity resolution to ensure incoming records integrate accurately with established person-matching processes.
• Review clinical terminology mappings and standardized vocabulary and concept assignments for newly integrated data.
• Perform end-to-end testing in nonproduction environments and support production releases and post-deployment monitoring.
• Incorporate newly onboarded data sources into reconciliation, monitoring, and observability processes.
• Evaluate data quality across completeness, conformance, and plausibility.
• Maintain data dictionaries and technical documentation covering newly available clinical datasets.
• Communicate the availability and usability of new datasets to downstream consumers.
• Manage multiple concurrent clinical data onboarding workstreams within an Agile, sprint-based delivery model.

Required experience and skills

• Strong SQL skills with hands-on BigQuery experience.
• Experience developing data ingestion and transformation pipelines with Airflow or comparable orchestration tools.
• Familiarity with the OMOP Common Data Model (CDM) and mapping clinical data across OMOP domains and tables.
• Knowledge of clinical terminology, standardized vocabularies, and concept mapping.
• Understanding of patient matching and identity resolution concepts.
• Experience validating newly onboarded datasets for completeness, conformance, and plausibility.
• Experience working in a GCP data analytics environment.
• Experience supporting testing, production deployment, data reconciliation, and post-release monitoring.
• Ability to independently manage multiple data-source onboarding efforts in an Agile delivery environment.