Job Description

• The medallion lakehouse (bronze / silver / gold) on the Microsoft data stack, implemented to the architect’s design and documented so every decision is reproducible.
• Automated extraction connectors for EHR / practice-management systems (target: 4 systems in year one), plus ingestion of clearinghouse 835 / 837 files and client-supplied feeds — replacing manual monthly pulls.
• A claim lineage database linking charges, claims, remittances, and payments across sources (target: ≥90% linkage rate), enabling true first-pass-resolution and denial analytics.
• Dimensional (star-schema) models for core RCM KPIs — first-pass resolution, days in AR, denial rates, net collection rate — serving certified Power BI semantic models.
• The automated validation harness inside the pipelines: row counts, reconciliation-to-source totals, period-over-period variance thresholds, and alerting — so errors are caught before a client sees them.
• A bounded InCredibly workstream: support for an in-flight client data migration and integration groundwork (API / FHIR) for the platform’s reporting needs.

• Own pipeline reliability end-to-end: orchestration, monitoring, failure recovery, schema-drift handling, and refresh SLAs.
• Absorb and document the architecture as it is built — decision records, runbooks, and standards — with the explicit goal of independent platform ownership within 6–12 months.
• Implement the technical half of data governance: lineage tracking, enforcement of certified metric definitions in the transformation layer, and role-based access to data assets.
• Integrate new data sources as clients onboard — API-based where available, structured file exchange (SFTP) where not.
• Handle PHI to HIPAA standards: minimum-necessary access, encryption in transit and at rest, and audit-ready handling in every pipeline.
• Work day-to-day with the associate data engineer; grow into a mentoring role as ownership expands.

• Strong SQL and solid Python for data engineering.
• Hands-on Azure data stack experience — Azure Data Factory plus Synapse, Fabric, or Databricks (equivalent lakehouse experience on another cloud considered with strong fundamentals).
• Has owned at least one pipeline or data product end-to-end — contributed to its design, built it, and operated it in production — as opposed to executing assigned tickets inside someone else’s build.
• Working knowledge of dimensional modeling applied in production.
• A demonstrated validation and reconciliation mindset: you can explain, concretely, how you knew your numbers were right. This is non-negotiable at any level.
• Disciplined handling of sensitive / regulated data; HIPAA or PHI exposure preferred.
• Evidence of fast learning and increasing scope — this role is a succession seat, and trajectory matters as much as current state.

• US healthcare claims and remittance data (835 / 837), EHR / practice-management exports, or RCM metrics exposure.
• FHIR / HL7 integration experience; REST API development.
• Power BI semantic-model / dataset design (the front end sits on your models).