Data Engineer - Hybrid / Remote

Job Details

Description

Data Engineer - Hybrid / Remote Opportunity

• Hybrid for candidates in Nashville and surrounding areas.
• Remote option available for candidates outside of surrounding areas.
  
  

This role requires a highly technical Data Engineer with expert-level proficiency in Azure Databricks, distributed data pipelines, and large-scale healthcare data processing. This role focuses on designing and implementing high-throughput ingestion pipelines, transactional lakehouse layers, and secure PHI data flows using Azure-native services and Databricks runtime optimizations.

You will build and operate production-grade data pipelines that meet rigorous requirements for security, lineage, compliance (HIPAA), observability, and operational SLAs, supporting analytics, AI, and clinical insights across the organization.

Core Responsibilities

Platform & Architecture

• Architect and implement scalable data processing pipelines using:
• Databricks Runtime (Apache Spark, Spark SQL, MLflow, Delta Lake)
• Delta Lake ACID transactions, Z-Ordering, OPTIMIZE, and Change Data Feed (CDF)
• Unity Catalog for governance, lineage, RBAC, and audit controls
• Design and enforce a medallion (Bronze/Silver/Gold) architecture with schema evolution, Delta Live Tables (DLT), and robust error-handling patterns
• Build high-performance ingestion frameworks for:
• FHIR and HL7 message streams
• X12 837/835 healthcare claims data
• EHR/EMR source systems
• Batch, real-time, and event-driven data sources
  

Azure Cloud Engineering

• Develop and operate data pipelines leveraging:
• Azure Data Lake Storage Gen2 (hierarchical namespace, ACLs, POSIX permissions)
• Azure Data Factory or Synapse Pipelines (parameterization, dynamic pipelines, triggers)
• Azure Event Hubs and/or Service Bus for streaming ingestion
• Azure SQL Database and Azure Synapse (Dedicated and Serverless pools)
• Azure Functions for lightweight orchestration and automation
• Azure Monitor, Log Analytics, and Application Insights for observability
• Implement enterprise-grade security including:
• VNet integration and private endpoints
• Secrets and key management using Azure Key Vault
• Managed identities and least-privilege access controls
  

Distributed Data Engineering

• Develop optimized PySpark and/or Scala pipelines using advanced Spark techniques:
• Catalyst optimizer tuning
• Cluster sizing and autoscaling strategies
• Adaptive Query Execution (AQE)
• Efficient join strategies (broadcast vs. shuffle)
• Build and maintain:
• High-volume batch ETL pipelines (100M records)
• Low-latency streaming pipelines using Spark Structured Streaming
• Implement CI/CD for Databricks environments, including:
• Git-integrated DEV/QA/PROD workspaces
• Automated job and workflow deployments
• Unit testing using pytest and Databricks testing frameworks
  

Healthcare Data & Compliance

• Design and implement secure PHI pipelines compliant with:
• HIPAA Privacy and Security Rules
• SOC 2 and HITRUST-aligned controls
• Build pipelines supporting healthcare data standards including:
• FHIR R4 resources (Patient, Encounter, Observation, Claim, etc.)
• HL7 v2.x messages (ADT, ORU, ORM)
• X12 EDI transactions (837, 835, 270/271)
• Ensure end-to-end lineage tracking, auditability, and data retention across all lakehouse layers
  

Required Qualifications

• 5 years of experience in modern data engineering roles
• Expert-level proficiency in:
• PySpark and Spark SQL
• Databricks (Jobs, Workflows, Repos, Delta Live Tables)
• Delta Lake architecture and transactional design patterns
• Azure Data Factory or Azure Synapse Pipelines
• Cloud-native data security (RBAC, ABAC, privilege boundary enforcement)
• Strong experience working with healthcare data formats and standards:
• FHIR (JSON)
• HL7 v2/v3
• X12 EDI claims data
• Deep understanding of distributed systems, data partitioning strategies, concurrency, and cluster resource tuning
  

Preferred Qualifications

• Experience implementing Unity Catalog at enterprise scale
• Familiarity with MLOps workflows and Databricks MLflow
• Experience using dbt with Databricks SQL
• Relevant certifications, including:
• Databricks Data Engineer Professional
• Microsoft Azure DP-203
• HL7 or FHIR certification (nice to have)
  
  

Benefits

• Comprehensive health, dental, and vision insurance
• Health Savings Account with an employer contribution
• Life Insurance
• PTO
• 401(k) retirement plan with a company match
• And more!
  
  

ENVIRONMENTAL/WORKING CONDITIONS: Normal busy office environment with much telephone work. Possible long hours as needed. The description is intended to provide only basic guidelines for meeting job requirements. Responsibilities, knowledge, skills, abilities and working conditions may change as needs evolve.

• If you are viewing this role on a job board such as Indeed.com or LinkedIn, please know that pay bands are auto assigned and may not reflect the true pay band within the organization.
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