The Senior Analytics Engineer will architect data pipelines, maintain analytics datasets, and collaborate with stakeholders to deliver actionable insights based on complex business questions.
ABOUT US
At Vida, we help people get better- and we're helping the healthcare system get better, too.
Vida is a virtual, personalized obesity care provider that uses evidence-based treatment to help patients manage obesity and related conditions like diabetes, high blood pressure, anxiety and depression. Vida's team of Obesity Medicine-Certified Physicians, Registered Dietitians, Expert Coaches and Licensed Therapists takes a whole-person approach to care, helping people lose weight, reduce stress and improve their overall health.
By combining advanced technology with top-notch healthcare providers, Vida is breaking down the barriers that have historically kept people from getting the best care. It's trusted by Fortune 100 companies, major national payers and large providers to enable their employees to live their healthiest lives.
Vida Health is seeking a Senior Analytics Engineer to serve as a high-impact, full-stack data partner. Positioned at the intersection of analytics engineering and data analysis, this role requires a practitioner who moves fluidly between technical development and strategic business partnership. You will own the entire lifecycle of data delivery- architecting pipelines from raw sources through dbt models and semantic layers into final Looker dashboards. You will embed directly with stakeholders to scope complex business questions, execute rigorous analyses, and independently translate ambiguous requirements into clear, decision-ready answers.
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.
Vida is proud to be an Equal Employment Opportunity and Affirmative Action employer.
Diversity is more than a commitment at Vida—it is the foundation of what we do. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, religion, gender, gender identity or expression, sexual orientation, marital status, national origin, genetics, disability, age, or Veteran status. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.
We seek to recruit, develop and retain the most talented people from a diverse candidate pool. We don’t just accept differences — we celebrate them, we support them, and we thrive on them for the benefit of our employees, our platform and those we serve. Vida is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.
We do not accept unsolicited assistance from any headhunters or recruitment firms for any of our job openings. All resumes or profiles submitted by search firms to any employee at Vida in any form without a valid, signed search agreement in place for the specific position will be deemed the sole property of Vida. No fee will be paid in the event the candidate is hired by Vida as a result of the unsolicited referral.
**Vida is authorized to do business in many, but not all, states. If you are not located in or able to work from a state where Vida is registered, you will not be eligible for employment. Please speak with your recruiter to learn more about where Vida is registered.
Please note: Applicants must be authorized to work in the U.S. as Vida is unable to sponsor work visas for any position.
All Vida Employees must reside in/be able to work from the U.S.- international work is prohibited. Job postings at Vida are evergreen and will remain open through end of year, until filled.
#LI-remote
Vida Health San Francisco, California, USA Office
100 Montgomery St, San Francisco, CA, United States, 94104
Similar Jobs
.png)
Logistics • Marketing Tech • Software
The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.
Top Skills:
BigQueryDbtLookerOmniPythonRedshiftSnowflakeSQLTableau
Software
Own and improve dbt models, ELT pipelines, and warehouse architecture (Snowflake or equivalent) to deliver reliable executive KPIs and metric governance. Build data spine for Finance/Operations, enforce data quality/testing, partner cross-functionally with Engineering, FP&A, and Accounting, and influence analytics engineering standards, tooling, and roadmap.
Top Skills:
BigQueryClarityDbtDbt Semantic LayerEltGa4HeapLookerMetricflowPythonRedshiftSigmaSnowflakeSQLStitchVertica
Information Technology • Software
Contract Senior Analytics Engineer to design and build a dbt-based datamart for onboarding an MMM/incrementality vendor. Translate vendor schema to internal DTC sources, implement dbt models, tests, and docs, configure Snowflake data sharing, and manage GitLab merge request workflows.
Top Skills:
AirflowDbt CloudDbt CoreGitlabMetricflowSnowflakeSQL
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
