Senior Analytics Engineer, Vida Health

• 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
• 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

Desirable

• 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
• 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