Data Engineer
Core
Design, build, and maintain scalable data pipelines and workflows to transform raw healthcare data (EHRs, claims, APIs) into clean, analytics-ready structures for leading healthcare organizations.
Role type
Data Engineer
Builds
Scalable data pipelines ingesting, transforming, and delivering data from diverse sources into analytics-ready structures
Domain
Healthcare technology / Data Engineering
Deliverable
production ML models | product features
Required skills
SQL (query optimization and debugging), Python, Cloud data platforms (Snowflake, Databricks, Azure Data Factory, AWS Redshift, Google BigQuery), ETL/ELT principles, Data warehousing, Data modeling, Orchestration frameworks (Apache Airflow)
Preferred skills
dbt, CI/CD pipelines, Git, DevOps workflows, Infrastructure-as-Code (Terraform, CloudFormation), Real-time/streaming data tools (Kafka, Kinesis, Pub/Sub), Containerization (Docker, Kubernetes)
Technologies
Snowflake, Databricks, Azure Data Factory, AWS Redshift, Google BigQuery, dbt, Apache Airflow, Kafka, Kinesis, Terraform, Docker
Responsibilities
Design and build scalable data pipelines; Transform raw data sources into clean, reliable data streams; Optimize data pipelines for performance; Manage multi-faceted work streams and meet deadlines
Seniority
Mid-level (2–5+ years experience)