Data Engineer (Healthcare)
RemoteUnited States
Job Summary
Design, build, and maintain scalable data pipelines and workflows that ingest, transform, and deliver data from diverse sources including EHRs, claims, APIs, and CRM systems into analytics-ready structures. Create clean, reliable data streams by applying ETL/ELT principles, data warehousing, and modeling best practices across the pipeline lifecycle. Work hands-on with cloud platforms such as Snowflake, Databricks, Azure Data Factory, AWS Redshift, or Google BigQuery to tackle new technical challenges. Collaborate closely with client stakeholders and internal teams to understand data needs and deliver reliable solutions. Contribute to a culture of knowledge-sharing and mentoring. Travel required for initial project kickoff and quarterly visits.
Required Qualifications
- 3–5+ years of professional experience in data engineering or a related role
- Strong SQL skills, including query optimization and debugging
- Proficiency in Python (or another programming/scripting language such as Scala or Java)
- Hands-on experience with at least one of: Snowflake, Databricks, Azure Data Factory, AWS Redshift, Google BigQuery
- Experience with dbt or similar transformation tools, and/or Apache Airflow or other orchestration frameworks
- Familiarity with ETL/ELT principles, data warehousing, and data modeling concepts
- Experience with cloud services (AWS, Azure, or GCP)
- Travel required: for the initial project kickoff, followed by quarterly visits.
Desired Qualifications
- Healthcare industry knowledge and experience (Epic, HL7, FHIR, claims data)
- Experience with CI/CD pipelines, Git, and DevOps workflows
- Familiarity with Infrastructure-as-Code tools (Terraform, CloudFormation)
- Experience with real-time/streaming data tools (Kafka, Kinesis, Pub/Sub)
- Containerization experience (Docker, Kubernetes)
- Relevant cloud or data tool certifications
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