Analytics Engineer

Summary

Join Vida, a virtual personalized obesity care provider, as an Analytics Engineer on the Data Foundations team. This new role focuses on building and monitoring data pipelines for various healthcare datasets, including medical claims, pharmacy, lab results, and biometric data. You will design and maintain scalable data models in DBT and BigQuery, ensuring data quality and accessibility for product, operations, and clinical teams. The ideal candidate possesses strong SQL/DBT skills, experience with healthcare data, and a desire to work at the intersection of infrastructure, data quality, and downstream impact. You will collaborate with data analysts and cross-functional stakeholders to improve data reliability and accessibility. This role requires experience with ETL/ELT orchestration tools and a strong understanding of healthcare data challenges, including handling PHI/PII in a HIPAA-compliant manner.

Requirements

• 3+ years in analytics engineering, data engineering or similar analytics-focused roles
• Strong experience with SQL and modern data modeling practices (e.g., dimensional modeling, star/snowflake schemas)
• Experience using DBT (preferred) or an equivalent transformation framework
• Familiarity with cloud data warehouses (ideally BigQuery; Redshift/Snowflake okay)
• Experience with ETL/ELT orchestration tools like Airflow or similar
• A strong understanding of healthcare data (especially claims, labs, pharmacy) and its common challenges
• Comfort handling PHI/PII, with familiarity around HIPAA-compliant analytics practices
• Excellent communication and collaboration skills across technical and non-technical teams

Responsibilities

• Monitor and support critical inbound pipelines for claims, pharmacy, lab and biometric data, ensuring completeness and timeliness
• Design and maintain scalable, modular DBT models on top of BigQuery to power internal analytics and performance guarantees
• Translate business logic and metric definitions into reusable, production-grade data transformations
• Partner with Data Analysts and cross-functional stakeholders to make healthcare data more reliable and accessible
• Contribute to data validation frameworks and observability across the analytics stack
• Support ingestion and mapping of complex structured healthcare data (e.g., FHIR, EHR, pharmacy claims) into proprietary canonical models
• Drive documentation, testing and data governance best practices across your work
• Participate in code reviews, schema design discussions and cross-team architecture decisions
• Ensure data integrity, quality and observability throughout the analytics stack
• Contribute to data governance, documentation and knowledge sharing across the data team
• Partner with engineering teams on data infrastructure and with business teams to align on key metrics and KPIs