Senior Data Engineer

Teal Health is hiring a Senior Data Engineer for a hybrid role in the United States, focused on building a data foundation that helps the rest of the company query trusted, analysis-ready models. In this contract position, you will own the data warehouse, ingestion, and the modeled Omni data layer, partnering with analytics so dashboards are consistent and well-defined. You will also work with sensitive health data in alignment with HIPAA and Teal’s data governance practices.

What you’ll own

• Data warehouse ownership: maintain the warehouse architecture while improving performance, reliability, and documentation.
• Ingestion with Fivetran: manage and extend Fivetran ingestion across source systems, including troubleshooting connector and schema issues.
• dbt transformation layer: build and maintain dbt models using a staging reporting pattern from raw sources to business-ready models used for forecasting, marketing, HubSpot, AWS, PostHog, and inventory.
• Omni data layer: define relationships, joins, and modeled fields so teammates can answer cross-system questions independently.
• Analytics enablement: collaborate with the analytics lead to ensure dashboards sit on an accurate, consistent, and well-defined data layer.
• Early integrations: take on integration work early, including connecting new data sources and supporting partner data flows.
• dbt tests and documentation: write tests and documentation so the team can trust and understand what’s in the warehouse.
• Data standards and team growth: set expectations for modeling, testing, and documentation, and support how the data team grows.
• Ticket-driven execution: work from a ticketed backlog (Jira or similar), scope requests across the company, and keep priorities visible.
• HIPAA-aligned data handling: handle sensitive health data carefully and in line with HIPAA and Teal’s data governance practices.

What you bring

• 5+ years of experience in data engineering or analytics engineering, including owning a production data warehouse.
• Strong SQL, including window functions, date logic, and complex joins across marketing, product, and operational data.
• Fluency in Postgres/Redshift/Snowflake-style SQL (for example, ::type casts, date_trunc(), and similar).
• Hands-on experience with dbt-core, including:
  • models and sources
  • dbt_project.yml and packages.yml configuration
  • Jinja templating
  • custom macros (for example, generate_schema_name)
  • dbt’s testing and docs framework
• Experience building a data warehouse using a layered staging reporting architecture.
• Experience working with Fivetran-landed data and comfort digging into each source’s raw schema quirks.
• Working knowledge of common dbt packages such as dbt_utils and dbt_date (for example, surrogate keys and date spines).
• A habit of clear documentation and organized, ticket-driven work.

Role details

• Location: United States (hybrid). Preferred Hybrid or Full-time in office (San Francisco); open to Remote-US.
• Department: Engineering
• Reports to: Head of Engineering
• Employment type: Contract (approximately 5-20 hours per week, projects may fluctuate)
• Hourly rate: $90–$125 per hour

Technologies you’ll work with

• SQL, Postgres, Redshift, Snowflake
• dbt-core, Jinja
• Fivetran
• dbt_utils, dbt_date
• Omni, HubSpot, PostHog, AWS
• HIPAA, Jira

Preferred

• Experience with Omni or a similar semantic/modeling layer (such as Looker or LookML).
• Python for scripting, integrations, or pipeline tooling.
• Experience with healthcare or EHR integrations.
• Deeper Jinja experience, including control flow and variables within dbt models.
• Experience at an early-stage or fast-growing company where you owned a data function with limited support.