Senior Analytics Engineer (Data + BI)

Location: Boston, MA (onsite)

What FamilyWell Offers

FamilyWell is an AI enabled mental health startup focused on solving the women’s mental health crisis by seamlessly embedding high quality, equitable, and affordable care into OB/Gyn practices. This role provides the chance to own the full data stack—from ingestion to BI—establish PHI governance, and empower self‑serve analytics across Care Ops, Business Ops, Sales, Partner Success, and Revenue Cycle. The position is based onsite in Boston, offering the opportunity to collaborate closely with cross‑functional teams and shape the analytics platform that informs critical care outcomes.

Responsibilities

• Platform ownership: maintain the data warehouse (Snowflake) and connect to source systems such as EMR, RCM, patient engagement, scheduling, and support tools. lead ELT efforts (Meltano today) with custom connectors when needed, and manage orchestration (dbt Cloud/CI). Own the company data strategy and the architectural design of replicas, the warehouse, and the BI layer.
• Modeling and metrics: build curated data marts and a governed semantic layer in dbt; define durable metrics like Time-to-Care, referral funnels, cancellations, provider capacity, and cohort outcomes. implement data quality tests (dbt tests, Great Expectations), track lineage, set up alerts, and drive rapid root-cause analysis.
• BI and enablement: administer the BI tool Sigma, manage roles and permissions, and deliver high‑impact dashboards. Conduct stakeholder discovery, translate questions into metrics and dashboards, and establish data contracts. Train teams on self‑serve best practices and maintain documentation.
• Security and compliance: apply HIPAA aligned controls including RBAC/ABAC, column‑level masking or tokenization, audit logging, data retention, and least‑privilege access.
• Reliability and cost: monitor performance, data freshness, and cost across the warehouse, ELT, and BI; optimize through 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.
• Strong SQL, experience with dbt (or comparable transformation tooling), and hands‑on work with a cloud data warehouse (Snowflake preferred; BigQuery, Redshift, or Databricks acceptable). Proficiency with a BI platform (Sigma preferred; Looker, Tableau, or Power BI acceptable).
• Git‑based CI/CD, Terraform, Docker.
• Solid 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, or dbt semantic models).
• Experience integrating healthcare data (EMR, RCM, claims, eligibility, scheduling, patient engagement); working knowledge of HL7/FHIR and healthcare data nuances (encounters, payers, CPT/ICD, denials).
• HIPAA and PHI practices (de‑identification, RBAC, audit logs) and familiarity with vendor BAAs.
• Strong stakeholder skills: requirements gathering, translating KPIs into metrics, and thorough documentation.

Nice to Have

• Experience with data reliability tooling such as Great Expectations, Monte Carlo, or Elementary.
• Background with CRM or support tools (Salesforce, HubSpot, Zendesk) and marketing or 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