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.