Staff Data Analytics Engineer
New
S
Sidecar HealthHealth insurance
Remote position but candidates must be based in California, Oregon, Washington, Utah, or Texas.Full-TimeStaff
SalaryCompetitive salary, bonus opportunity, and equity package
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Job Details
- Experience
- 6+ years of experience in analytics or data engineering (or a closely related role)
- Required Skills
- PythonSQLSnowflakedbtHIPAA
Requirements
- Have 6+ years of experience in analytics, data engineering, or a closely related role building and maintaining data models and pipelines.
- Hold a bachelor’s degree in Computer Science, Mathematics, Statistics, Economics, or a related technical field, or have equivalent professional experience.
- Bring strong SQL and dbt skills, including incremental models and testing.
- Have hands-on Snowflake experience, including semantic modeling.
- Have experience building data quality tests and monitoring.
- Have experience working with product teams to define metrics and scope ambiguous problems.
- Be fluent with AI coding tools such as Claude and able to use and validate AI-generated code.
- Be comfortable working with privacy and compliance requirements in a regulated environment.
- Bring end-to-end ownership from raw data through to trusted metrics.
- Communicate effectively with technical and non-technical partners.
Responsibilities
- Design, build, and maintain dbt and semantic models in Snowflake for reliable, documented product metrics.
- Build ingestion and transformation pipelines when needed, aligning with data engineering on shared infrastructure and standards.
- Develop AI-ready semantic models, metric definitions, and documentation for Cortex and CoWork agents.
- Partner with Product and Engineering on data capture, structure, and modeling decisions.
- Translate product roadmap goals and feature hypotheses into measurable success metrics.
- Identify data collection gaps and drive their resolution with Product and Engineering.
- Analyze product decisions and feature performance, including experiment readouts and significance testing when needed.
- Use AI coding tools and Snowflake Cortex, then review, test, and validate generated code and outputs.
- Build HIPAA considerations and role-based and row-level access controls into data designs.
- Review SQL, dbt, and AI-generated code and document models, metric definitions, and design decisions.
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