Piper Companies is hiring a Senior Data Engineer for a rapidly growing, tech-enabled healthcare organization located in the DMV area. The Senior Data Engineer will build and scale a modern AWS and Databricks-based data platform, developing reliable data pipelines and analytics-ready datasets to support clinical operations and business insights. The Senior Data Engineer is a direct placement opportunity and will ideally be hybrid in the DMV area, working closely with Engineering and Product teams in a fast-paced environment.

Responsibilities of the Senior Data Engineer:

• Design, build, and maintain scalable data pipelines using API ingestion, CDC, and event-driven architectures
• Develop and manage dbt models to transform raw data into clean, analytics-ready datasets
• Implement data quality checks, monitoring, and observability to ensure pipeline reliability
• Partner with engineering and product teams to deliver scalable data solutions and reporting capabilities
• Optimize performance, scalability, and cost-efficiency of AWS and Databricks data systems
• Support dashboards and analytics initiatives that drive operational and clinical insights
  
  

Requirements of the Senior Data Engineer:

• 5+ years of experience in data engineering, building production-grade pipelines and ingestion frameworks
• Prior healthcare or regulated data environment experience required
• Strong proficiency with AWS, SQL, Python, and Databricks
• Experience with data ingestion patterns (API, CDC, streaming) and orchestration tools such as Airflow or Databricks Workflows
• Strong communication skills and ability to collaborate with cross-functional teams
• Bachelor’s degree in Computer Science, Engineering, or a related technical field
  
  

Compensation for the Senior Data Engineer:

• $140,000–$180,000, based on experience
• Full Comprehensive Benefits: Health, Vision, Dental, PTO, Paid Holiday and Sick Leave if Required by Law
  
  

This job opens for applications on July 10, 2026. Applications for this job will be accepted for at least 30 days from the posting date.

Keywords: Data Engineer, AWS, Databricks, dbt, SQL, Python, Healthcare Data, CDC, Data Pipelines, Airflow, Spark, PySpark, Streaming, Lakehouse

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