SQL Database Engineer

• Extract, transform, and validate patient clinical data from EMR/EHR systems using HL7 v2.x, CCDA, and FHIR bundles.
• Interpret HL7 segments (PID, PV1, ORC, OBR, OBX, DG1, RXA, etc.) for clinical measure mapping.
• Troubleshoot inconsistent or malformed HL7 messages and resolve data quality gaps with vendors.
• Build robust parsing logic to normalize data across heterogeneous EMR systems.

EMR/EHR Database Querying & Measure Data Retrieval

• Query EMR databases (NextGen, eCW, Greenway, Athena, etc.) to extract structured and unstructured clinical data required for MIPS measures.
• Understand vendor-specific table schemas, metadata dictionaries, and proprietary data models.
• Translate measure specifications into SQL logic based on CMS MIPS calculation rules.
• Validate measure completeness, timeliness, and accuracy prior to client submission.

Technical Standards, Architecture Alignment & Governance

• Maintain and enforce engineering implementation standards, documentation requirements, and build methodologies.
• Ensure all engineering work aligns with defined solution architecture, technology standards, and security baselines.
• Lead efforts to improve standard configurations, automation, templates, and reusable frameworks.
• Ensure engineering quality and consistency through audits, peer reviews, and structured validation.

Data Pipeline Engineering & Transformation

• Build scalable ingestion pipelines using SQL, Spark (batch & streaming), Python, Databricks, EMR, or OCI Data Flow.
• Develop metadata-driven pipelines supporting multiple clients and EMR platforms.
• Implement data quality frameworks (DQ checks, thresholds, reconciliation reports).
• Maintain robust lineage, audit trails, and governance compliance for CMS readiness.

Regulatory Data Support for MIPS & Value-Based Care

• Support MIPS Advisors with extraction of numerator/denominator data for clinical quality measures.
• Produce audit-ready documentation and reproducible calculations for CMS submission.
• Map EHR data elements to CMS measure logic, identifying gaps or vendor remediation needs.
• Validate that clients meet annual CMS submission timelines and data completeness requirements.

Cross-Functional Collaboration

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• Translate technical data issues into actionable insights for non-technical MIPS Advisors.
  • Coordinate with EMR vendors to resolve data extraction failures or schema changes.