Sr. Analytics Engineer

Privia Health•Remote, USA

1h•$102,000 - $120,000•Remote

About The Position

As Privia Health continues to expand, the Analytics team requires an agile and tech-savvy Healthcare Analytics Engineer to bridge the gap between complex raw healthcare data and strategic business operations. In this role, you will design, model, and maintain robust analytics infrastructure by combining advanced SQL practices, BI tooling, and analytics engineering principles. You will sit at the intersection of payer claims (medical, pharmacy, attribution), Electronic Medical Record (EMR/EHR) clinical data, and operational feeds, transforming disparate sources into clean, centralized analytical datasets. Operating in a fast-paced environment, you will empower operational teams, clinical leaders, and business stakeholders with trustworthy insights, rapid ad-hoc query support, and scalable data models that support broad healthcare initiatives—including Value-Based Care (VBC) performance, clinical workflow optimization, and enterprise reporting.

Requirements

Bachelor’s degree in Healthcare Analytics, Data Science, Computer Science, Health Informatics, Information Systems, or a related quantitative field preferred, or equivalent practical experience.
3+ years of professional experience in Healthcare Analytics, Analytics Engineering, or Business Intelligence within a provider group, health system, payer, or healthcare technology environment.
Strong domain experience working with both payer claims data (medical, pharmacy, eligibility/attribution) and EMR/clinical data (e.g., Athenahealth, Epic, Cerner).
Advanced SQL skills: Expert-level ability to write complex queries, multi-table JOINs, CTEs, window functions, query optimization, and data transformation routines.
Exposure to modern analytics engineering workflows and tools (e.g., dbt, Python/Pandas, Git/version control, cloud data warehouses like Snowflake, MS SQL Server, or BigQuery), and Excel.
Familiarity with general healthcare operational metrics as well as Value-Based Care (VBC) concepts (such as risk scores/HCC, quality metrics, and shared savings calculations).
Proven ability to operate in an agile, fast-paced environment, balancing structured long-term engineering projects with rapid, ad-hoc query requests.
Strong interpersonal and communication skills, with a track record of effectively explaining technical data modeling concepts to operational and clinical stakeholders.

Responsibilities

Design, build, and maintain production-ready data models and semantic layers using advanced SQL and analytics engineering best practices to support enterprise reporting and self-service analytics.
Ingest and blend diverse healthcare datasets—including payer claims, attribution rosters, quality measure extracts, EMR/clinical data, and operational logs.
Execute fast-turnaround ad-hoc SQL queries and deep-dive analyses to answer pressing operational, clinical, and financial questions across various business units.
Define and standardize core business metrics across operational domains, including practice operations, provider utilization, clinical quality measures, and VBC performance tracking.
Partner closely with cross-functional stakeholders (IT, Operations, Clinical Support, Payer Relations) to gather requirements, translate operational needs into technical logic, and iterate quickly in an agile environment.
Conduct automated data validation, quality assurance testing, and performance tuning on data warehouse queries and transformation jobs to maintain data integrity.
Serve as an internal SME on data structures, clinical workflows, and payer data layouts, assisting non-technical teams in interpreting underlying data accurately.
Document data models, logic definitions, and data flow pipelines and collaborate with BI teams to ensure transparency and consistency across the enterprise analytics landscape.
Other duties as assigned.