Data Engineer

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
  
• 5+ years of hands-on experience in data engineering (cloud-native environments preferred).
  
• Strong proficiency in SQL and Python for data engineering workflows.
  
• Proven experience with:
  
• Google Cloud Dataflow, Datastream, or Airbyte (streaming & ingestion pipelines)
  
• AWS Postgres (transactional & analytical use cases)
  
• Google FHIR Store (FHIR APIs & EHR ingestion)
  
• Google BigQuery (large-scale data warehouse/lakehouse)
  
• dbt/OBT for transformations and modeling
  
• Experience designing and maintaining unified data models from heterogeneous healthcare data sources.
  
• Familiarity with healthcare data standards: HL7, FHIR, X12 EDI (837/835), ICD, SNOMED, ADT, CCD/CCDA.
  
• Experience ensuring HIPAA-compliant data handling, governance, and observability.
  
• Knowledge of data modeling (star/snowflake schemas) and cloud-native architectures (AWS/GCP).
  

Good to Have

• Experience with Health care standardization frameworks.
  
• Building feature stores for AI/ML pipelines.
  
• Familiarity with real-time streaming.
  
• Hands-on with Power BI or other BI tools for analytics enablement.
  
• Prior work in Value-Based Care, ACOs, MSOs, or population health environments.
  
• Ability to mentor junior engineers and establish team-wide best practices.
  
  

• Build impactful data pipelines powering AI, LLMs, and BI in healthcare.
  
• Work on meaningful problems that directly improve patient outcomes and provider efficiency.
  
• Be part of a growing tech-first healthcare company with strong domain expertise.
  
• Collaborative culture with AI, data, product, and engineering teams.
  
• Competitive compensation, benefits, and career growth opportunities.