Sidecar Health - Staff Data Analytics Engineer
Requirements
• 6+ years of experience in analytics or data engineering (or a closely related role), building and maintaining data models and pipelines • Bachelor’s Degree in Computer Science, Mathematics, Statistics, Economics, a related technical field, or equivalent professional experience • Strong SQL and dbt skills, including incremental models and testing • Hands-on Snowflake experience, including semantic modeling • Commitment to data quality, with experience building tests and monitoring that catch issues before stakeholders do • Experience working with product teams, ideally technical ones, to define metrics and scope ambiguous problems • Fluency with AI coding tools like Claude, with the judgment to use, build, and validate AI-generated code • Comfort working in a regulated environment with privacy and compliance requirements • The ownership and end-to-end thinking to see a problem from raw data to a metric someone trusts • Strong communication skills with technical and non-technical partners • Snowflake Cortex, CoWork agents, or other LLM-based tooling • Working knowledge of statistics and experimentation • Healthcare, claims, or insurance background; HIPAA familiarity • Python for pipelines or lightweight applications • Fivetran or other ELT experience, including troubleshooting sync and CDC issues • Tableau or other BI tools • What You'll Get • What You'll Get • Competitive salary, bonus opportunity, and equity package • Comprehensive Medical, Dental, and Vision benefits • A 401k retirement plan • Paid vacation and company holidays • Opportunity to make an impact at a rapidly growing mission-driven company transforming healthcare in the U.S.
Responsibilities
• Design, build, and maintain dbt models and semantic models in Snowflake that give product teams a reliable, well-documented view of key metrics • Build the pipelines behind those models when needed, from ingestion through transformation, and align with data engineering on shared infrastructure and standards • Build AI-ready data: semantic models, metric definitions, and documentation that let Cortex and CoWork agents answer business questions accurately • Guide data design decisions with Product and Engineering, including what data gets captured, how it’s structured, and how it’s modeled, so we can measure results from day one • Partner with product managers to turn roadmap goals and feature hypotheses into measurable success metrics • Identify gaps in data collection and drive them to resolution with Product and Engineering • Provide analysis to inform product decisions and evaluate feature performance, including occasional statistical work such as experiment readouts and significance testing • Use AI coding tools and Snowflake Cortex to speed up development, and review, test, and validate AI-generated code and outputs before they ship • Build compliance into your designs, including HIPAA considerations and role-based and row-level access controls • Review SQL, dbt, and AI-generated code for correctness, not just style, and raise the technical standard for the team • Document models, metric definitions, and design decisions so others can build on them
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