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/MetricFlow, 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.
- Experience with Power BI as a downstream consumer of a semantic layer (preferred).
- Experience preparing data for AI/BI tools such as Genie or LLM applications (preferred).
Welldoc operates in ISO 13485 and MDSAP regulated and HITRUST and SOC 2 Type II compliant environments. Therefore, it is expected that all employees will have either prior experience working in those environments or will be trained to understand the requirements needed to work and support those requirements and culture as they relate to individual roles and responsibilities.
Required Education
- Bachelor's degree in Computer Science, Data Science or Business Analytics is preferred. A Masters Degree in a relevant field may substitute for some required experience.
Compensation & Benefits
Welldoc offers a competitive compensation package which, in addition to salary, includes generous PTO, medical insurance, dental insurance, vision care, life and disability insurance, retirement benefits. and the opportunity to participate in health savings accounts and/or dependent care accounts. While the anticipated salary range for this position is between $110,000 - $130,000/year with the expectation that most candidates will fall around the midpoint of the range. Exceptional candidates may exceed the range if education and experience warrant.
