Senior Data Engineer

Why this role exists

Every prediction we make depends on data arriving correctly from systems we do not control. One operator runs PointClickCare, the next runs HCHB, WellSky, or something else, and their feeds differ in protocol, convention, and reliability. A model that trains on degraded data does not throw an error; it quietly gets worse at detecting deterioration.
Our moat is the corpus itself: 70,000 years of continuous vital signs joined to clinical records from more than 400,000 unique patients. Critical information travels among our platform, EHRs, and internal systems that patients depend on, and all of it relies on a high quality bar. You will own that layer.

What you'll own

• Pipelines and integrations. Customer EHR systems and hospital databases via REST, webhooks, and CDC or log shipping including Microsoft SQL Server.
• Clinical data. Transform, validate, and normalize ADT, conditions, medications, notes, and vitals across HL7 v2 and FHIR.
• The warehouse. Schemas serving real-time application needs and downstream ML, optimized for performance and cost across Snowflake and MySQL.
• Reliability. Pipelines in AWS with monitoring, alerting, and the data-quality checks that catch silent degradation before a model does.
• Compliance. HIPAA and SOC 2 across every pipeline, with sound PHI handling.

Required Qualifications

• 5+ years in data or backend engineering
• Building high-throughput pipelines from ingestion through transformation and storage
• Strong Python and SQL
• Hands-on Snowflake and MySQL, including schema design and performance tuning
• Production experience in AWS
• Experience with sensitive or regulated data

Preferred

• EHR integrations (PointClickCare, Homecare Homebase, WellSky, Epic), HL7 v2, FHIR, or CDC from SQL Server
• Supporting ML teams in production
• Significant open source, systems that outlived your tenure, or a high-bar engineering background