Vida Health
Healthcare
SeniorAnalyticsEngineer
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“Senior Analytics Engineer at Vida Health. Skills: Analytics Engineering, Data Analysis, dbt, LookML. Architect analytics-ready datasets. Maintain analytics-ready datasets”
What You'll Achieve.
deliver high-impact solutions; prove program efficacy
Industry & Context.
rigorous analyses; translate ambiguous requirements into clear, decision-ready answers; Think critically about data limitations; challenge baseline assumptions
Applicants must be authorized to work in the U. S., All Vida Employees must reside in and be able to work from the U. S.
What They're Looking For.
Must Have
Bachelor’s degree, 5-7 years of senior-level experience spanning both analytics engineering and data analysis, Advanced SQL proficiency, production-level dbt experience, Fluent in LookML, Version control and CI workflows experience, modern cloud data warehouses
Nice to Have
Proven track record of driving initiatives within the digital health and healthtech sectors, Understanding of claims, clinical, and patient engagement data ecosystems, strict adherence to HIPAA guidelines and PHI data governance, Experienced in launching data-driven experiments, building patient cohort analyses, measuring outcomes to prove program efficacy
What You'll Do.
Architect analytics-ready datasets
Maintain analytics-ready datasets
Architect LookML explores
Maintain LookML explores
Architect high-impact dashboards
Maintain high-impact dashboards
Confidently navigate dbt
Make modeling decisions
Partner directly with Member Engagement teams
turn strategic questions into rigorous analyses
Collaborate strategically with core data engineering team
understand foundational data models
shape foundational data models
optimize foundational data models
Think critically about data limitations
challenge baseline assumptions
articulate necessary caveats
How You'll Work.
Team & Collaboration
Partner directly with Member Engagement teams; Collaborate strategically with the core data engineering team; articulate insights alongside their necessary caveats to both technical and non-technical audiences
Communication Scope
Exceptional communication skills; track record of managing stakeholders directly; scoping ambiguous requirements; delivering high-impact solutions independently; articulate insights alongside their necessary caveats to both technical and non-technical audiences
Process & Methodology
independently executing projects end-to-end without hand-offs, scoping ambiguous requirements, delivering high-impact solutions independently
Full Job Description
## Description 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,
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