Responsibilities:
- Architect and maintain analytics-ready datasets, LookML explores, and high-impact dashboards.
- Confidently navigate dbt to trace lineage and debug models.
- Make modeling decisions (grain, incremental strategies, data contracts) that bring order and stability to messy raw data sources.
- Partner directly with Member Engagement teams to turn strategic questions into rigorous analyses.
- Collaborate strategically with the core data engineering team to understand, shape, and optimize foundational data models.
- Think critically about data limitations, challenge baseline assumptions, and articulate insights alongside their necessary caveats to both technical and non-technical audiences.
- Other duties as assigned.
Qualifications:
- Bachelor’s degree at a minimum.
- 5-7 years of senior-level experience spanning both analytics engineering and data analysis. You are a true full-stack data practitioner capable of independently executing projects end-to-end without hand-offs.
- Advanced SQL proficiency alongside production-level dbt experience, with specific expertise configuring metric and semantic layers.
- Comfortable navigating, testing, and contributing to non-trivial codebases utilizing dbt macros, exposures, and lineage.
- Version control and CI workflows experience within modern cloud data warehouses (e.g., Snowflake, BigQuery, Redshift).
- Fluent in LookML with a proven ability to author and refactor models, structure intuitive explores for self-service, and seamlessly bridge the gap between dbt models and downstream business users.
- Exceptional communication skills with a track record of managing stakeholders directly, scoping ambiguous requirements, and delivering high-impact solutions independently.
Preferred:
- Proven track record of driving initiatives within the digital health and healthtech sectors.
- Understanding of claims, clinical, and patient engagement data ecosystems, with a strict adherence to HIPAA guidelines and PHI data governance.
- Experienced in launching data-driven experiments, building patient cohort analyses, and measuring outcomes to prove program efficacy.
Skills Required
- Bachelor's degree
- 5-7 years of senior-level experience in analytics engineering and data analysis
- Advanced SQL proficiency
- Production-level dbt experience
- Experience with modern cloud data warehouses
- Fluent in LookML
- Exceptional communication skills
What We Do
Vida is a virtual care company that combines a human-centric approach with technology to address chronic and co-occurring physical and behavioral health conditions. We provide personalized chronic condition management combined with health coaching and therapy through a mobile and online platform that supports individuals in managing and significantly improving conditions such as diabetes, hypertension, obesity, depression, anxiety, etc. Our platform integrates deeply individual expert care with machine learning and remote monitoring to deliver lasting behavior change, health outcomes and cost savings. Vida is in the business of enabling self-insured employers, health plans and providers to take better care of their employees and members. We are trusted by Fortune 1000 companies, major national payers, and large providers to activate, engage, and empower their employees to live their healthiest lives. Based in San Francisco, CA, Vida is backed by investors including Khosla Ventures, StartX, Aspect Ventures, Canvas, Workday, and Nokia.


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