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Senior Data Engineer

Commure

Salary not specified
Oct 6, 2025
San Francisco, CA, US
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Commure is looking to transform the healthcare industry by simplifying administrative healthcare services through AI solutions. The company needs to build and optimize its data infrastructure to handle large-scale patient-related data securely, performantly, and compliantly, enabling analytics, observability, and secure development workflows.

Requirements

  • Strong SQL expertise with PostgreSQL and experience tuning queries for high-volume transactional databases
  • Hands-on experience with Python, Java, and SQL for data processing and pipeline orchestration
  • Familiarity with ClickHouse or other analytical databases, and data lake formats (Iceberg, Parquet, ORC)
  • Experience with AWS Glue (ETL, catalog) and S3-based data lakes
  • Understanding of cloud-native services in both Google Cloud (Cloud SQL) and AWS
  • Knowledge of data anonymization and governance techniques for sensitive healthcare data (HIPAA familiarity a plus)
  • Experience with monitoring/observability tools for data infrastructure (e.g., Grafana, dbt metrics, or custom solutions)

Responsibilities

  • Design, implement, and optimize ETL/ELT pipelines for large-scale PostgreSQL datasets (11TB+ production, 5TB staging)
  • Build scalable ingestion workflows into ClickHouse Cloud using Iceberg tables on AWS S3 and AWS Glue
  • Develop processes for anonymizing and preparing healthcare data in staging environments to support development and research without exposing PHI
  • Implement robust validation and reconciliation checks to ensure data quality and HIPAA-compliant handling
  • Develop and maintain schemas to support both OLTP (PostgreSQL) and OLAP (ClickHouse/Iceberg) workloads
  • Build tools and dashboards to monitor schema changes, query performance, and pipeline health across PostgreSQL, ClickHouse, and Glue/S3
  • Integrate structured healthcare data flows between EHR systems, RCM platforms, and internal services

Other

  • Proven experience in data engineering at scale (multi-TB datasets, OLTP + OLAP systems)
  • Strong problem-solving and debugging skills; ability to balance technical rigor with business needs
  • Effective communicator and collaborator across engineering, analytics, and product teams
  • Employees will act in accordance with the organization’s information security policies, to include but not limited to protecting assets from unauthorized access, disclosure, modification, destruction or interference nor execute particular security processes or activities.
  • Employees will be required to attest to these requirements upon hire and on an annual basis.