Senior Data Engineer (Contract)
About The Position
Teal Health is hiring a Senior Data Engineer to own its data warehouse, data pipelines, and modeled data layer in Omni. The role will maintain the path from raw data sources to trusted, analysis-ready models as the company expands its patient, payer, and provider relationships. Teal’s data sources include its backend, HubSpot, PostHog, AWS, and marketing and advertising platforms, with ingestion through Fivetran and transformations in dbt. The engineer will focus on pipelines, the warehouse, and the semantic layer, partnering with Analytics on dashboards and visualizations. This is a contract role expected to involve approximately 5–20 hours per week, with workload varying as projects change. The preferred arrangement is hybrid or full-time in the San Francisco office; remote work within the United States is also considered. The role reports to the Head of Engineering and handles sensitive health data in accordance with HIPAA and Teal’s data governance practices.
Requirements
- At least 5 years of experience in data engineering or analytics engineering, including ownership of a production data warehouse.
- Strong SQL skills, including window functions, date logic, and complex joins across marketing, product, and operational data.
- Fluency in Postgres-, Redshift-, or Snowflake-style SQL, including type casts and date_trunc().
- Hands-on dbt-core experience with models and sources, dbt_project.yml and packages.yml configuration, Jinja templating, custom macros, and dbt testing and documentation.
- Experience designing and developing a data warehouse using a layered staging-to-reporting architecture.
- Experience with Fivetran-landed data and investigating raw schema differences across sources, including advertising platforms, Google Search Console, Google Sheets, HubSpot, PostHog, AWS, and internal application databases.
- Working knowledge of common dbt packages such as dbt_utils and dbt_date, including surrogate keys and date spines.
- Clear documentation habits and experience with organized, ticket-driven work.
Nice To Haves
- 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 owning a data function with limited support.
Responsibilities
- Own the data warehouse, including its architecture, performance, reliability, and documentation.
- Manage and extend Fivetran ingestion across source systems, and troubleshoot connector and schema issues.
- Build and maintain dbt transformations using a staging-to-reporting pattern for business-ready models, including forecasting, marketing, HubSpot, AWS, PostHog, and inventory data.
- Own the Omni data layer by defining relationships, joins, and modeled fields for cross-system analysis.
- Partner with the analytics lead so dashboards use accurate, consistent, and well-defined data.
- Take on early integrations work, including connecting new data sources and supporting partner data flows.
- Write dbt tests and documentation so the team can trust and understand the warehouse.
- Set standards for data modeling, testing, and documentation, and help shape the growth of the data team.
- Work from a ticketed backlog such as Jira, scope requests from across the company, and keep priorities visible.
- Handle sensitive health data in line with HIPAA and Teal’s data governance practices.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Career Level
Senior
Education Level
No Education Listed
