Senior Analytics Engineer
New
V
Virta HealthHealthcare analytics
Corporate roles: We currently do not hire in the following states: AK, DE, HI, ME, MS, OK, SD, VT.Full-TimeSenior
Salary161,500 - 209,000 USD per year
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Job Details
- Experience
- 5+ years of experience in analytics engineering, data engineering, or a related technical role
- Required Skills
- PythonSQLGoData modelingBigQuerydbt
Requirements
- Have 5+ years of experience in analytics engineering, data engineering, or a related technical role, including shipping and supporting production data solutions.
- Demonstrate advanced SQL skills and sound data-modeling judgment, including reasoning about join cardinality, aggregation, historical state, and event sequences.
- Bring substantial hands-on dbt experience, including modular transformations, incremental models, testing, documentation, and dependency management.
- Have experience developing LookML views, Explores, dimensions, and measures, diagnosing join behavior, and maintaining consistent metric definitions.
- Have experience with BigQuery or a comparable cloud data warehouse, including query optimization and tradeoffs among freshness, performance, and cost.
- Apply software engineering practices such as version control, code review, automated testing, and controlled deployments.
- Have working proficiency in Python or Go for scripting, validation, and automation.
- Translate ambiguous business requirements into reusable technical solutions and explain tradeoffs clearly.
- Debug data issues across source systems, transformation pipelines, and BI tools, and take responsibility for the reliability and usability of delivered work.
- Have practical experience using AI-assisted development tools and validate generated SQL, code, and documentation against actual data behavior.
Responsibilities
- Design and implement reusable dbt models and BigQuery datasets that accurately represent core business concepts.
- Build and maintain LookML views, Explores, measures, and supporting dashboards with consistent business logic and clear documentation.
- Implement defined components of the data rearchitecture and Looker Core migration, reconcile results, validate downstream dependencies, and help retire legacy models and content.
- Work with Analytics, Finance, Growth, Customer Success, and Clinical partners to clarify data definitions and edge cases and build reusable solutions.
- Implement automated tests for model behavior, relationships, freshness, and business rules; investigate discrepancies and resolve production issues.
- Optimize SQL, materializations, incremental processing, and BigQuery partitioning and clustering.
- Contribute governed datasets, semantic definitions, and contextual documentation for agents and AI; validate agent answers against trusted queries and metrics.
- Own work from technical scoping through deployment and iteration, review code, share reusable patterns, and use AI-assisted development tools.
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