Data Engineer
Chesterfield Office Hybrid or Remote
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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