Data Engineer

Why You'll Want to Join! Join a leading Revenue Cycle Management (RCM) company dedicated to transforming healthcare data into actionable insights. We leverage cutting‑edge technology to streamline financial and operational processes, improving efficiency and patient outcomes. Job Type : Full-time Location : Chesterfield Office Hybrid or Remote Position Overview Lead the modernization of our data infrastructure as a Data Engineer. You'll architect scalable cloud‑native pipelines using Microsoft Fabric and Databricks to transform healthcare data—claims, EMR/EHR, HL7/FHIR—into actionable insights that drive revenue cycle optimization and clinical outcomes. Why This Role Matters Healthcare data engineering is mission‑critical: clean, governed data flows directly impact financial accuracy, compliance, and the decisions that improve patient care. Your ETL/ELT pipelines enable our analytics and data science teams to unlock the full potential of healthcare data. Key Responsibilities Design, build, and optimize ETL/ELT pipelines using Azure Synapse, Databricks, and Snowflake Develop robust data models and schemas for healthcare datasets, including claims, EMR/EHR, HL7, and FHIR standards Write and optimize SQL queries for performance across large healthcare datasets Implement data governance, quality frameworks, and HIPAA compliance controls Collaborate with analytics, data science, and business teams to define data requirements Monitor and troubleshoot data pipeline health and performance Develop Python or Scala code for complex transformations and data processing Support Power BI and analytics teams with data modeling and performance optimization Document data lineage, transformations, and technical architecture Requirements 3+ years of professional data engineering or ETL/ELT development experience Expert‑level SQL skills with proven optimization experience Proficiency in Python, Scala, or similar data processing languages Hands‑on experience with cloud data platforms (Azure Synapse, Snowflake, Databricks, or equivalent) Understanding of healthcare data standards (HL7, FHIR, claims data structures) Strong grasp of data modeling, normalization, and schema design Experience with data versioning, CI/CD pipelines, and data quality frameworks Preferred Qualifications Experience with Microsoft Fabric or Azure Data Factory Knowledge of HIPAA compliance and healthcare data security Background in healthcare, RCM, or claims processing Experience with dbt (data build tool) or equivalent transformation frameworks Exposure to dimensional modeling and data warehousing best practices What Success Looks Like In 90 days: Deploy first cloud pipeline to production; complete HIPAA training; establish data quality baseline metrics In 6 months: Reduce data pipeline latency by 30%; expand healthcare data models to include new sources; build reusable transformation components Ongoing: Maintain 99.5%+ pipeline uptime; mentor junior engineers; drive architectural improvements for scale and performance #J-18808-Ljbffr