Note: The job is a remote job and is open to candidates in USA. FamilyWell Health is an AI-enabled mental health start-up focused on addressing the women’s mental health crisis through integrated care solutions. The Senior Analytics Engineer will be responsible for managing the end-to-end data stack, including data ingestion, warehousing, and business intelligence, while ensuring compliance and data governance across various operational teams.

Responsibilities

• 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
• 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
• 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
• Implement HIPAA-aligned controls: RBAC/ABAC, column-level masking/tokenization, audit logging, data retention, and least-privilege access
• Monitor performance, freshness, and cost (warehouse, ELT, BI); optimize with SLAs for priority datasets

Skills

• 4–7+ years in analytics engineering / data engineering / BI engineering, including end-to-end ownership of ELT→BI
• 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; experience 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
• Data reliability tooling (Great Expectations/Monte Carlo/Elementary)
• Background with CRM/support tools (Salesforce/HubSpot/Zendesk) and marketing/scheduling data

Company Overview