Senior Analytics Engineer - Virta Health

About the Role

We’re looking for a Senior Analytics Engineer to build the trusted data models and analytics capabilities that help Virta operate and improve care at scale. This is a hands-on technical role working alongside other data & analytics engineers with both engineering and business stakeholders. You will write SQL and dbt models, develop shared LookML, investigate data discrepancies, and ship tested solutions into production.

Our stack includes BigQuery, dbt Cloud, and Looker/LookML. Near-term priorities include advancing our data and Looker modernization, expanding self-service analytics, and building governed data capabilities & a semantic layer for agents and AI.

Responsibilities

• Build reusable analytical models: Design and implement dbt models and BigQuery datasets that represent core business concepts accurately.
• Develop shared semantics: Build and maintain LookML views, Explores, measures, and supporting dashboards to keep business logic consistent.
• Deliver modernization work: Implement defined components of our data rearchitecture and Looker Core migration.
• Turn business questions into technical solutions: Partner with Finance, Growth, Customer Success, and Clinical teams to build reusable solutions.
• Own data quality: Implement automated tests for model behavior, freshness, and business rules. Investigate and resolve production issues.
• Improve performance: Optimize SQL, materializations, incremental processing, and BigQuery partitioning/clustering.
• Build for AI: Contribute governed datasets and semantic definitions to support data-agent implementations and ML workflows.
• Raise the engineering bar: Own work from technical scoping through deployment, code review, and iteration.

Must-Haves

• 5+ years of experience in analytics engineering, data engineering, or a related technical role.
• Advanced SQL skills and strong data-modeling judgment (join cardinality, aggregation, historical state).
• Substantial hands-on experience with dbt (modular transformations, incremental models, testing).
• Experience developing LookML views, Explores, and dimensions.
• Experience with BigQuery or a comparable cloud data warehouse.
• Strong software engineering practices (version control, code review, automated testing).
• Working proficiency in Python or Go.
• Ability to translate ambiguous business requirements into technical solutions.
• Practical experience using AI-assisted development tools.

Bonus Points

• Experience migrating analytical models or BI platforms.
• Experience building semantic layers or data tools for AI agents.
• Experience preparing reusable datasets for ML.
• Experience with GCP, Airflow, Dagster, or data observability tools.
• Experience working with healthcare or sensitive data (HIPAA, PHI/PII).