Data Engineer

About Privia Health

Privia Health is a technology-driven national company focused on empowering physicians by partnering with medical groups, health plans, and health systems to enhance practices, improve patient care experiences, and reward high-value care delivery in both in-person and virtual environments. The Privia Platform combines expert leadership, scalable operational processes, and complete cloud-based technologies to lower unnecessary healthcare costs, achieve superior patient outcomes, and promote provider well-being.

Role Overview

As a Data Engineer on the Data Engineering team, you will be responsible for designing, building, and sustaining data pipelines and infrastructure critical for clinical, financial, and operational reporting. You will manage healthcare data such as payer attribution files, claims, eligibility data, and quality measures, overseeing pipeline ownership end-to-end in a production environment.

Key Responsibilities

• Develop data pipelines to ingest, transform, and deliver healthcare datasets through staging, transformation, and mart layers.
• Create and maintain dbt models adhering to established design conventions ensuring testability, documentation, and optimal performance.
• Implement data validation tests, monitor the health of pipelines, investigate anomalies, and guarantee the accuracy of reports derived downstream.
• Write complex, efficient SQL queries for data transformation, analysis, and troubleshooting.
• Develop Python scripts for file processing, API integration, customized ETL logic, and automation tasks.
• Maintain continuous operational oversight of assigned pipelines, including job monitoring, failure troubleshooting, vendor coordination, and maintaining operational guides.
• Collaborate with analytics, clinical, and operations teams to translate business needs into technical solutions, communicating clearly about project progress and obstacles.
• Participate actively in Agile/Scrum processes using tools like Jira and GitLab, involving sprint planning, code reviews, QA testing, and releases.
• Continuously seek improvements to enhance pipeline efficiency, reduce manual interventions, increase testing coverage, and eliminate technical debt.

Required Qualifications

• Minimum of three years experience as a Data Engineer, Analytics Engineer, or similar position.
• Proficient in advanced SQL with the ability to author complex queries, optimize their execution, and resolve data-related issues independently.
• At least two years of Python experience developing production-grade scripts for file handling, API interaction, and data processing.
• Two or more years experience using dbt for writing models, tests, and macros.
• Experience with Snowflake or similar cloud data warehouses like BigQuery, Redshift, or Databricks for a minimum of two years.
• Knowledgeable about data warehouse design patterns, including star schema, slowly changing dimensions, and layered architectures.
• Familiarity with ETL/ELT workflows and batch data processing techniques.
• Experience with version control systems (Git) and continuous integration/continuous deployment practices.
• Hands-on experience working with raw data formats such as CSV, pipe-delimited files, JSON, XML, and Parquet.

Additional Information

Confidentiality will be maintained throughout your application process as per EEO guidelines.

The base salary range for this role is $77,000 to $90,000 annually, exclusive of bonuses and benefits such as medical, dental, vision, life, pet insurance, 401(k), paid time off, and wellness programs. An annual bonus of approximately 15% is also part of the compensation. Salary decisions will consider experience, education, and location.

Technical Requirements for Remote Work

Remote employees must have a reliable internet connection with a minimum bandwidth of 5 Mbps download and 3 Mbps upload. Internet speed should be verified before starting employment. Employees frequently working from home may receive expense reimbursement for related costs.

Inclusion & Diversity

Privia Health fosters an inclusive culture, encouraging individuals from diverse backgrounds and experiences to apply regardless of age, race, disability, religion, gender identity, veteran status, or any legally protected status.