Note: The job is a remote job and is open to candidates in USA. Privia Health is a technology-driven national physician enablement company that collaborates with medical groups, health plans, and health systems. They are seeking a Senior Data Quality Analyst to play a key role in testing and implementing advanced reporting and analytics tools, while designing and maintaining data quality frameworks to ensure the accuracy and consistency of enterprise data.
Responsibilities
- Leverage AI-Assisted data quality practices including
- GenAI based rule generation and test case creation
- Intelligent anomaly detection and pattern recognition
- Automated Triage and Summarization of Data quality issues
- Develop and automate data quality checks and controls using SQL, Python in Snowflake environment
- Implement data validation, reconciliation and anomaly detection logic across batch and streaming data pipelines
- Embed Automated Data quality checks into ETL/ELT pipelines to enforce quality gates and prevent defective data from propagating downstream
- Build reusable data quality automation components, libraries and frameworks that can be consistently adopted across data engineering teams
- Comply with and contribute to departmental standards related to data, data governance, project planning, validation and documentation
- Validate BI datasets, semantic models and dashboards by ensuring:
- Source-to-report data reconciliation
- Metric and KPI accuracy
- Aggregation, filter and refresh correctness
- Familiarity with value based care and fee for service delivery models
- Apply interoperability standards (HL7, X12 FHIR) to ensure systems communicate reliably and securely
- Monitor and report on data quality metrics, and trends, including dashboard level data accuracy and consistency
- Enable AIOps-style data observability using AI-driven insights to proactively identify data drift, schema changes and metric anomalies
- Support governance and audit readiness by ensuring data quality controls, validations, and dashboard certifications are documented and traceable
- Continuously improve data quality practices through automation, standardization and AI-driven enhancements, reducing manual validation effort
- Serve as a technical mentor and subject matter expert for the team, coaching newer engineers, driving knowledge sharing, establishing best practices, and promoting the adoption of AI-enabled data quality and automation frameworks across the organization
Skills
- 4+ years of experience in Data Quality Engineering, with a strong focus on automation, and frameworks with a solid understanding of data quality dimensions (Accuracy, completeness, consistency, timeliness and validity)
- 4+ years of experience with SQL for data profiling, reconciliation and validation
- 4+ years of experience implementing automated data quality frameworks embedded within ETL/ELT workflows
- 3+ years of proven experience working in a Snowflake environment, supporting large-scale data pipelines and analytics platforms
- Proven experience of working within technical and business professionals in a matrix management environment, managing multiple priorities and deadlines
- Proven clearly demonstrated experience in problem solving, data management and implementation
- Demonstrate advanced experience of leveraging AI for data validation, lineage, and pipelines
- Solid grounding of healthcare specific data exchange standards
- Strong communication skills with the ability to translate business reporting requirements into technical quality standards
- Bachelor's degree in relevant field (Computer science, engineering or related technical field preferred)
Benefits
- Bonuses or benefits (medical, dental, vision, life, and pet insurance, 401K, paid time off, and other wellness programs)
- Annual bonus targeted at 15%
- Employees who regularly work from home offices are eligible for expense reimbursement to offset this cost.
Company Overview
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