Senior Analytics Engineer (Data + BI)

Own the end-to-end data stack—from ingestion and warehousing to modeling and BI—while establishing governance for PHI and enabling self-serve analytics across Care Ops, Business Ops, Sales, Partner Success and Revenue Cycle.

Responsibilities

• Platform ownership: manage the Snowflake warehouse, connect to source systems (EMR, RCM, patient engagement, scheduling, support tools), implement ELT (Meltano) and orchestration (dbt Cloud/CI), and define the data strategy and architecture for replicas, the warehouse, and BI tooling.
• Modeling and metrics: design and maintain curated data marts and a governed semantic layer in dbt; establish durable metrics such as Time-to-Care, referral funnels, cancellations, provider capacity, and cohort outcomes; add data quality tests (dbt tests, Great Expectations), track lineage, set alerts, and drive rapid root-cause resolution.
• BI and enablement: administer the BI platform (Sigma), manage roles and permissions, and deliver high-impact dashboards; lead stakeholder discovery to translate questions into metrics, dashboards, and data contracts; train teams on self-serve analytics and maintain documentation.
• Security and compliance: enforce HIPAA-aligned controls including RBAC/ABAC, column-level masking or tokenization, audit logging, data retention policies, and least-privilege access.
• Reliability and cost optimization: monitor performance, data freshness, and costs across warehouse, ELT, and BI; optimize with SLAs for priority datasets.

Requirements

• 4–7+ years in analytics engineering, data engineering, or BI engineering, with end-to-end ownership of ELT and BI.
• Proficiency in advanced SQL, dbt or equivalent transformation tooling, and a cloud data warehouse (Snowflake preferred; BigQuery, Redshift, or Databricks acceptable); strong experience with a BI platform (Sigma preferred; Looker, Tableau, or Power BI acceptable).
• Git-based CI/CD, Terraform, and Docker experience.
• Strong Python skills for lightweight transformations and connector development; experience with an 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/claims/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 experience (Great Expectations, Monte Carlo, Elementary).
• Background with CRM or support tools (Salesforce, HubSpot, Zendesk) and marketing/scheduling data.

Technologies

• Snowflake
• Postgres
• Meltano
• dbt / dbt Cloud
• Great Expectations
• Sigma
• LookML
• Looker
• Tableau
• Power BI
• Git
• Terraform
• Docker
• Python
• Airflow
• Prefect
• Dagster
• Airbyte
• Singer SDK
• Fivetran
• Stitch
• Healthie
• Spruce
• Candid
• Hubspot
• Quickbooks
• EMR
• RCM
• HL7
• FHIR
• Salesforce
• Zendesk