The posting
Location: Preferred Hybrid or Full-time in Office (San Francisco); open to Remote-US Employment Type: Contract (~5-20 hours per week as projects fluxuate) Department: Engineering Reports to: Head of Engineering
About Teal Health:
At Teal Health, we’re on a mission to provide women with the tools, access, and resources they need to make informed decisions about their health, starting with cervical cancer screening.
We believe it’s time to redesign women’s health and put women, their preferences, and their experiences at the center. By offering women the choice to self-collect from the comfort and convenience of home, we can expand access to life-saving preventive care and help eliminate cervical cancer in the U.S.
Our Values:
We boldly champion the future women deserve. And we do this through our values, which are to elevate women, expect exceptional, and learning, every day. The Teal team lives our values and uses them to guide our decisions when building Teal.
About Teal Health:
At Teal Health, we’re on a mission to provide women with the tools, access, and resources they need to make informed decisions about their health, starting with cervical cancer screening.
We believe it’s time to redesign women’s health and put women, their preferences, and their experiences at the center. By offering women the choice to self-collect from the comfort and convenience of home, we can expand access to life-saving preventive care and help eliminate cervical cancer in the U.S.
Our Values:
We boldly champion the future women deserve. And we do this through our values, which are to elevate women, expect exceptional, and learning, every day. The Teal team lives our values and uses them to guide our decisions when building Teal.
Why We Are Hiring For This Role
Teal Health is looking for a Senior Data Engineer to own the foundation that every decision at Teal runs on: our data warehouse, our pipelines, and the modeled data layer in Omni that the rest of the company queries. As Teal reaches more patients, payers, and provider partners, the questions we need to answer are getting harder and the data behind them is getting messier. This person will own that layer end to end, from raw source to trusted, analysis-ready models.
Teal’s data now spans our own backend, HubSpot, PostHog, AWS, and a long list of marketing and ad platforms. All of it is landed through Fivetran and transformed in dbt. We need someone who ensures our data is reliable and easy to access. This role will focus on our data pipelines, the warehouse, and the semantic layer underneath and partner with Analytics on dashboarding and visualizations.
What You’ll Do
- Own Teal’s data warehouse, including its architecture, performance, reliability, and documentation.
- Manage and extend Fivetran ingestion across our source systems, and troubleshoot connector and schema issues as they come up.
- Build and maintain our dbt transformation layer. It follows a staging → reporting pattern from raw sources to business-ready models for forecasting, marketing, HubSpot, AWS, PostHog, and inventory.
- Own the Omni data layer: define the relationships, joins, and modeled fields that let teammates answer cross-system questions on their own.
- Partner with our analytics lead so dashboards sit on a data layer that is accurate, consistent, and well-defined.
- Take on integrations work early on, including connecting new data sources and supporting partner data flows.
- Write tests and documentation in dbt so the team can trust and understand what’s in the warehouse.
- Set standards for data modeling, testing, and documentation, and help shape how the data team grows.
- Work from a ticketed backlog (Jira or similar), scoping requests from across the company and keeping priorities visible.
- Handle sensitive health data with care and in line with HIPAA and Teal’s data governance practices.
What We’re Looking For
Required
- 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 (::type casts, date_trunc(), and similar).
- Hands-on experience with dbt-core: models and sources dbt_project.yml and packages.yml configuration Jinja templating custom macros (e.g. generate_schema_name) dbt’s testing and docs framework
- Experience designing and developing 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. Our sources include: ad platforms: Google, Meta, TikTok, Bing, Reddit, Pinterest, Quora, Spotify Ads Google Search Console and Google Sheets HubSpot, PostHog, and AWS internal application databases
- Working knowledge of common dbt packages like dbt_utils and dbt_date (surrogate keys, date spines, and so on).
- A habit of clear documentation and organized, ticket-driven work.
Preferred
- Experience with Omni or a similar semantic/modeling layer (Looker, LookML, etc.).
- 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.
The expected hourly rate for this contract role is $90 – $125 per hour. Actual compensation within this range is based on factors such as skills, experience, location, and qualifications.
