Architect the initial dbt project structure and establish modeling patterns for our EHR integration layer.
Design and build foundational data models that normalize and standardize data from diverse EHR systems (Epic, Cerner, NextGen, etc.).
Establish data quality frameworks, testing strategies, and observability patterns for the EHR integration layer.
Create reusable transformation patterns and documentation that enable rapid integration of new EHR data sources.
Collaborate with product and engineering teams to define data contracts and specifications for the EHR layer.
Build resilient data pipelines that handle the complexities of healthcare data (HL7, FHIR, proprietary formats).

Requirements

5+ years of data engineering development experience with a focus on cloud-based data pipelines and infrastructure.
Strong experience architecting greenfield data platforms and establishing foundational patterns.
Expertise with dbt, including project architecture, macros, testing strategies, and documentation.
Deep expertise in SQL and data modeling (dimensional modeling, normalization strategies).
Experience with healthcare data standards (HL7, FHIR, X12) is a strong plus.
Expertise in relational and columnar databases (Snowflake, Postgres).
Experience with data orchestration tools (Airflow, Dagster, Temporal, etc).
Excellent communication and documentation skills - you'll be establishing patterns others will follow.
Bachelor's or Master's in Computer Science, Engineering, or a related field, or equivalent experience.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

dbtSQLdata modelingdimensional modelingnormalization strategiesdata pipelinesdata quality frameworkstesting strategiesdata transformationhealthcare data standards

Soft Skills

communicationdocumentation

Certifications

Bachelor's in Computer ScienceMaster's in Computer ScienceBachelor's in EngineeringMaster's in Engineering