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Data Engineer

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Job Description - Data Engineer



Full-time


Description

Data Engineer

Chesterfield Office Hybrid or Remote

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. We are looking for a Data Engineer to help optimize data pipelines and build a next-generation data infrastructure incorporating technologies such as Microsoft Fabric, Azure Synapse, Databricks, and Snowflake.

Position Overview

Lead the modernization of our data infrastructure as a Data Engineer for nimble. 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


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