Data Engineer
Job in
Chesterfield, St. Louis city, Missouri, 63005, USA
Listed on 2026-05-07
Listing for:
Nimble
Full Time
position Listed on 2026-05-07
Job specializations:
-
IT/Tech
Data Engineering, Data Analyst, Data Science Manager, Data Warehousing
Job Description & How to Apply Below
Data Engineer
Chesterfield Office Hybrid or Remote
Position OverviewLead 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 MattersHealthcare 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
- 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
- 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
- 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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