The Role

Data Engineer

We are looking for a Data Engineer to join our fully remote team and help build the foundation for WellTheory’s next stage of growth. In this role, you’ll design and scale the data infrastructure that powers everything from our AI-native Care Hub to client-facing analytics, ensuring that our systems remain fast, reliable, and insight-rich as we scale 📊

You’ll partner closely with our Head of Product, engineering team, Head of Finance, Data Analyst, Care Team, and Marketing stakeholders to design data models, pipelines, and tools that support better decision-making, improve care delivery, and enable the next generation of product features. This is a unique opportunity to shape both our data architecture and strategy at a company that’s redefining how people with autoimmune conditions receive care.

You likely have 5+ years of experience as a data engineer or software engineer working with data infrastructure at scale. Our current stack includes BigQuery, Postgres, and Superset, with services built in Node.js and deployed on GCP. Experience with Kafka, Aftivemq, Python, Kubernetes, and Argo CD - or similar - highly desired. You don’t need experience with every part of our stack — we’re confident an experienced engineer with strong fundamentals can ramp quickly.

Some of your responsibilities may include:

• Designing, building, and maintaining scalable and secure data pipelines that collect, clean, and transform data from multiple sources (product, care operations, member engagement, and client reporting). This includes validating, ingesting, and normalizing data from our external sources like SFTP files from our B2B2C partners and making files available to internal stakeholders for operations in a secure way
• Auditing and improving our existing BigQuery and Superset setup to strengthen data reliability, optimize performance, and reduce costs.
• Modeling and documenting data architecture to support analytics, product insights, and internal tools, ensuring consistent definitions across the business.
• Partnering with Product and Engineering to instrument new product features with clean, trustworthy data for analysis and AI use cases.
• Developing frameworks for data quality, testing, and observability that increase confidence in our metrics and dashboards.
• Collaborating cross-functionally to support reporting and analytics needs across care delivery, operations, and client success.
• Contributing to data strategy and best practices as we grow the function — helping WellTheory evolve toward a data-first, insight-driven culture.

About You

These are not requirements but describe someone who might be a great fit for WellTheory and this role:

• Builder mindset. You love designing elegant, reliable data systems from scratch and take pride in laying clean, maintainable foundations that scale with the business.
• Full-stack data experience. You’ve built pipelines, managed warehouses, modeled data for analytics, and understand the needs of both technical and non-technical stakeholders.
• Strong collaborator. You’re comfortable partnering with engineers, product managers, and operations leaders to translate messy, real-world problems into scalable data solutions.
• Analytically minded. You think in terms of accuracy, observability, and performance — ensuring the right data gets to the right people (and systems) at the right time.
• Hands-on and strategic. You can dive into SQL in the morning and help shape WellTheory’s long-term data architecture in the afternoon.