Senior Healthcare Data Engineer – Epic Clarity/Caboodle

Quoris, LLC•Philadelphia, PA

19d•Hybrid

About The Position

We are seeking a Senior Healthcare Data Engineer to support the migration and modernization of enterprise data workloads into Microsoft Azure and Microsoft Fabric for a healthcare organization. This role will design, develop, and maintain production-grade ingestion and transformation solutions spanning Epic Clarity, Epic Caboodle, SQL Server, and other clinical, operational, financial, and third-party data sources. The Senior Healthcare Data Engineer will serve as the primary data engineering resource responsible for building and operating trusted healthcare data pipelines that move Epic and enterprise data into Microsoft Azure and Fabric for analytics, AI, operational reporting, and governed self-service use. This individual will translate reporting and analytics requirements into scalable data products, strengthen data quality and lineage, and migrate legacy ETL workloads into a governed Lakehouse and Data Warehouse architecture. The ideal candidate brings a rare combination of healthcare data fluency, deep SQL engineering expertise, and hands-on Microsoft Fabric delivery experience.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Engineering, Health Informatics, or a related field; or equivalent relevant experience.
5+ years of progressive data engineering, ETL, or data warehouse experience including production support for business-critical data platforms.
3+ years of hands-on experience in a hospital, health system, payer, or healthcare analytics environment.
Demonstrated production experience with Epic Clarity and Epic Caboodle including complex healthcare data extraction, reconciliation, and downstream modeling.
Deep SQL Server and T-SQL expertise including complex stored procedures, query optimization, execution-plan analysis, indexing, and ETL performance tuning.
Hands-on experience building data ingestion and transformation solutions in Microsoft Fabric, Azure Data Factory, Azure Synapse, or closely related Azure data services.
Proficiency with Fabric Data Pipelines, notebooks, Lakehouse and Warehouse patterns, Spark, PySpark, Python, and SQL.
Experience implementing data quality controls, operational logging, monitoring, auditing, error handling, and restartable pipeline patterns.
Experience with Git-based development, CI/CD, environment promotion, and release management.
Working knowledge of healthcare privacy, security, and regulatory expectations for handling PHI and sensitive enterprise data.

Nice To Haves

Epic Clarity Data Model certification and Epic Caboodle certification; Epic Cogito Fundamentals, Reporting Workbench, or SlicerDicer credentials are additional assets.
Microsoft Certified: Fabric Data Engineer Associate, Azure Data Engineer Associate, or another relevant Microsoft data platform credential.
Experience migrating SSIS, SQL Agent, stored-procedure, or other legacy workloads to Microsoft Fabric or Azure.
Experience with OneLake, Delta Lake, Direct Lake, Power BI semantic models, and enterprise data certification practices.
Experience with Microsoft Purview, data cataloging, lineage, metadata management, or formal data governance programs.
Familiarity with healthcare interoperability standards including HL7 v2, FHIR, and API-based integration patterns.
Experience with Azure Key Vault, private networking, managed identities, service principals, and cloud security controls.

Responsibilities

Design, build, and maintain end-to-end data pipelines using Microsoft Fabric Data Factory, Data Pipelines, Dataflows Gen2, notebooks, Lakehouse, Warehouse, OneLake, and related Azure data services.
Implement robust full-load, incremental, change-based, and restartable ingestion patterns for on-premises and cloud data sources.
Develop transformations using PySpark, Spark SQL, Python, T-SQL, and Power Query appropriate to each workload.
Implement Medallion Architecture patterns across Bronze, Silver, and Gold layers, preserving raw source fidelity while producing curated, consumption-ready data products.
Extract, model, reconcile, and optimize healthcare data sourced from Epic Clarity and Caboodle for clinical, patient access, revenue cycle, financial, quality, and operational analytics.
Design, develop, and optimize complex T-SQL, stored procedures, views, functions, staging tables, data marts, and ETL control structures.
Embed automated data quality checks for completeness, validity, uniqueness, consistency, referential integrity, timeliness, and source-to-target reconciliation.
Apply least-privilege access, encryption, audit logging, and appropriate PHI controls across all data pipelines and reporting outputs.
Use GitHub Enterprise or Azure DevOps for source control, branching, pull requests, code review, and controlled environment promotion.
Monitor pipeline health, triage production incidents, conduct root-cause analysis, and implement durable corrective actions.
Partner with Epic application, Cogito, analytics, and business teams to validate source meaning, extraction logic, and downstream dependencies.
Conduct code walkthroughs, peer reviews, and knowledge-transfer sessions that strengthen internal engineering capability.