Salary
💰 $150,000 - $195,000 per year
Tech Stack
AirflowBigQueryPythonSQL
About the role
- Build foundational data models that enable Color to demonstrate the value of our programs to employer clients and prospective customers.
- Understand both the source data and the needs of the business in order to design robust, scalable models that support insightful analysis and accurate measurement.
- Collaborate cross-functionally with Product, Engineering, Operations, GTM, and Client teams — navigating ambiguity with clarity, and evaluating scope/impact tradeoffs to deliver the most meaningful solutions.
- Define and maintain business logic in our dbt models, ensuring our warehouse evolves in sync with the changing landscape of our business, product, and source data.
- Build self-service views and semantic layers that “speak the language” of data consumers, empowering them to gain deep insights independently through intuitive self-service resources.
- Partner with BI and analytics stakeholders to align on metric definitions, ensuring consistency, trust, and transparency across dashboards and reports.
- Spot patterns in recurring requests and design durable, reusable solutions that reduce ad hoc work and maximize scale.
- Apply emerging AI and automation tools to accelerate analytics workflows and increase team efficiency.
- Contribute to a culture of data-driven decision-making by mentoring peers and sharing best practices in analytics engineering.
Requirements
- 5+ years of experience using data to drive product growth and operational efficiency.
- 3+ years of experience as an analytics engineer or in a similar role.
- Excellent communication skills and ability to work with technical and non-technical partners from many teams, especially in exploring decisions and trade-offs.
- Experience driving complex projects from design to completion.
- Advanced proficiency in SQL, data model design, and data warehouse platforms.
- Working knowledge of Python and data science tools.
- Deep interest in the modern data stack.
- Commitment to software engineering best practices and applying them in an analytics setting.
- A strong desire to work at the intersection of healthcare and technology, driven by the opportunity to make preventive care more accessible and equitable.
- A strong desire to adapt to new emerging technology and AI tools to scale the output of the team.