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.