Senior Data Engineer

Responsibilities

• Lead development of the agentic connector pipeline to automate source profiling, field mapping, and dbt model generation
• Design and build AI-assisted data ingestion workflows using LLM APIs and agentic orchestration frameworks
• Own the first end-to-end agent-built connectors as proof of concept
• Establish internal AI tooling standards and mentor the team on agentic development practices
• Design, build, and maintain data pipelines and systems to meet business needs
• Implement data quality control processes and contribute to observability frameworks
• Document new and existing systems, designs, processes, and procedures
• Participate in an on-call rotation (3–9% of the year)

Requirements

• 5+ years of experience in data engineering or a related field
• 1–2+ years of hands-on experience building with LLM APIs and agentic frameworks
• Strong Python and SQL proficiency
• Experience with Databricks and AWS
• Strong understanding of data lake architecture, data modeling, and medallion patterns
• Experience building and consuming APIs
• Experience with data quality control and pipeline observability
• Strong debugging, problem-solving, and analytical skills
• Excellent written and verbal communication skills

Preferred Qualifications

• Experience with dbt and modern data transformation patterns
• Familiarity with healthcare data formats such as CCDAs, 837s, FHIR APIs, CDS Hooks, or HL7
• Experience with Tuva or similar clinical data normalization frameworks
• Knowledge of Value-Based Care and Accountable Care Organizations
• Experience with EHR integrations (Epic, NextGen, Athena, ECW)
• Familiarity with orchestration tools like Databricks Workflows or Airflow
• Experience in a startup or high-growth environment