FamilyWell - Senior Analytics Engineer (Data + BI) — Healthcare
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Requirements
• Must-have • 4–7+ years in analytics engineering / data engineering / BI engineering, including end-to-end ownership of ELT→BI. • end-to-end • Proficiency with: advanced SQL, dbt (or comparable transformation tooling), a cloud data warehouse (Snowflake preferred; BigQuery/Redshift/Databricks acceptable), and a BI platform (Sigma preferred; Looker/Tableau/Power BI acceptable) • Git-based CI/CD, Terraform, Docker. • Strong Python skills for light transformations and connector development; dexperience with an EL/ingestion framework (Meltano preferred; Airbyte, Singer SDK, Fivetran, or Stitch acceptable) and an orchestrator (Airflow, Prefect, Dagster, or similar) • Experience designing semantic layers (LookML, Metrics Layer, dbt semantic models). • Experience integrating healthcare data (EMR/RCM/claim/eligibility/scheduling/patient engagement); working knowledge of HL7/FHIR and healthcare data quirks (encounters, payers, CPT/ICD, denials). • HIPAA/PHI practices (de-identification, RBAC, audit logs) and vendor BAA familiarity. • Strong stakeholder skills: requirements gathering, translating KPIs, and documentation. • Nice-to-have • Data reliability tooling (Great Expectations/Monte Carlo/Elementary). • Background with CRM/support tools (Salesforce/HubSpot/Zendesk) and marketing/scheduling data. • Our stack (target) • Our stack (target) • Sources: Registry (Postgres), Healthie (EMR), Spruce (Patient Messaging), Candid (billing/RCM), Hubspot (CRM), Quickbooks (Accounting). • Sources • Warehouse: Snowflake • Warehouse
Responsibilities
• Platform ownership • Platform ownership • Maintain a warehouse (Snowflake) and connect it to source systems (EMR, RCM, patient engagement, scheduling, support tools). • Implement ELT (currently using Meltano) (plus custom connectors when needed) and orchestration (dbt Cloud/CI). • Own company data strategy, detailed architecture and design of replica, warehouse, and BI tool. • Modeling & metrics • Modeling & metrics • Build curated marts and a governed semantic layer in dbt; define durable metrics (e.g., Time-to-Care, referral funnels, cancellations, provider capacity, cohort outcomes). • Add data quality tests (dbt tests/Great Expectations), lineage, and alerts; resolve root causes quickly. • BI & enablement • BI & enablement • Administer BI tool (currently Sigma), define roles/permissions, and ship high-leverage dashboards. • Drive stakeholder discovery; translate questions into metrics, dashboards, and data contracts. • Train teams on self-serve best practices and documentation. • Security & compliance • Implement HIPAA-aligned controls: RBAC/ABAC, column-level masking/tokenization, audit logging, data retention, and least-privilege access. • Reliability & cost • Reliability & cost • Monitor performance, freshness, and cost (warehouse, ELT, BI); optimize with SLAs for priority datasets.
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