Clinical Data Engineer

Job description

A leading organization is seeking a Clinical Data Engineer to enhance and maintain clinical analytics data pipelines based on the OMOP Common Data Model. The engineer will focus on extending structured clinical datasets with additional metadata while creating repeatable patterns that can scale across tables and domains.

The position requires strong SQL and BigQuery expertise, hands-on data pipeline development, OMOP CDM knowledge, and experience working within a GCP analytics environment.

Responsibilities

• Assess source-level metadata, including document identifiers, source attribution, and tracking identifiers, and determine how those attributes should flow through applicable OMOP domains.
• Develop SQL and pipeline changes that introduce metadata fields across prioritized OMOP tables.
• Support phased data releases covering both historical backfills and incremental data loads.
• Create reusable implementation patterns that allow additional metadata attributes and clinical domains to be incorporated consistently.
• Validate data accuracy, completeness, and continued availability to downstream consumers following each deployment.
• Coordinate the sequencing and prioritization of enhancements with clinical data stakeholders and downstream teams.
• Support user acceptance testing, defect resolution, and production deployments throughout each rollout.
• Maintain technical documentation and data dictionaries covering new attributes, lineage, and intended usage.
• Communicate implementation progress and data availability to downstream consumers.
• Manage multiple table and domain enhancements concurrently within an Agile, sprint-based delivery environment.

Required experience and skills

• Advanced SQL skills with hands-on BigQuery experience.
• Working knowledge of the OMOP Common Data Model (CDM).
• Experience modifying schemas and data pipelines across multiple OMOP domains and tables.
• Experience developing and maintaining data pipelines using Airflow or comparable orchestration technology.
• Experience implementing historical backfill and incremental loading patterns.
• Experience working in a GCP data analytics environment.
• Ability to independently manage multiple concurrent data engineering workstreams within Agile delivery cycles.
• Strong technical documentation skills, particularly for defining repeatable engineering patterns that can be adopted by other engineers.