Analytics Engineer, Semantic Layer

Company & Culture

Welldoc is driven by a powerful mission: empowering better health across conditions through AI-powered, personalized health tech, with a vision to be the leading clinically trusted AI tech partner across the healthcare industry. We're a team passionate about leveraging cutting-edge science to improve lives, united by core values of collaborative innovation, accountability to excellence, customer focus, efficiency, and unwavering integrity, quality, and safety.

At Welldoc, you'll thrive in a collaborative and innovative environment where your contributions directly impact our mission. Recognized as a Great Place to Work for the past five years and named to Modern Healthcare’s Best Places to Work 2026, as well as being an industry thought leader featured at SXSW and in the Wall Street Journal and Economist, we invite you to make a real difference in healthcare with us.

Job Purpose

This role sits on the Reporting & Visualization (analytics) team. You’ll design and build the semantic layer that defines how Welldoc measures its business. That layer will power our BI dashboards and our AI-driven applications. This is an individual contributor role real leadership scope. You’ll be the team’s go-to expert on the data model. You’ll set modeling standards, help shape data governance, and influence how analysts, engineers, and business stakeholders use data.

This role is a fit if you…

• Like owning a data model end to end: the business definitions, the build, and the long-term upkeep.
• Enjoy sitting with analysts and stakeholders, understanding their questions, and turning them into clean, reusable metrics.
• Are comfortable with ambiguity and would rather shape the plan than follow one.
• Want to work in person with a small, collaborative team.

Resposibilities

• Semantic layer:
  Design and build our consumption layer using Databricks Unity Catalog metric views. This includes defining measures, dimensions, joins, and business logic once so they can be reused everywhere.
• The data model:
  Evaluate our current Silver and Gold structures and recommend changes. Then lead the buildout of the new model with a focus on usability, performance, and scale.
• Requirements:
  Partner with analysts, data engineers, and business stakeholders to turn business questions into well-scoped technical requirements.
• BI and AI consumption:
  Make sure the layer serves Power BI reporting, self-service analytics, and AI tools such as Databricks Genie and LLM-based applications.
• Standards and governance:
  Help establish modeling conventions, documentation, data quality checks, and metric definitions. Work alongside our Data Governance Council.
• Engineering rigor:
  Bring version control, testing, modular design, and automation to analytics workflows.
• Tooling:
  Evaluate new tools and features as our stack evolves, and recommend what’s worth adopting.
• Troubleshooting:
  Diagnose data issues and explain root causes and fixes clearly to non-technical stakeholders.

Required Skills & Experience

• 3–5 years designing and building data models and transformations specifically for analytics use cases.
• 3+ years of hands‑on Databricks experience, including Unity Catalog and the medallion (Bronze/Silver/Gold) architecture.
• Hands‑on experience building a semantic or metrics layer. Databricks metric views are strongly preferred, and dbt Semantic Layer/Metric Flow, LookML, Cube, or Power BI semantic models are relevant too.
• Advanced SQL, working Python, and Git‑based development workflows.
• A track record of translating ambiguous business needs into concrete data models and metric definitions.
• Clear written and verbal communication, especially with non‑technical audiences.
• A proactive, ownership‑driven mindset. You spot problems and opportunities before anyone asks.
• Exp…