Senior Azure Data Engineer Python, PySpark & Databricks

Charlotte, United States | Posted on 09/09/2026

Axiom Path is an AI-first recruiting and staffing firm delivering RPO, MSP, and direct-hire solutions to enterprise clients across the U.S. Our team of experienced recruiters, supported by purpose-built automation, moves faster and communicates better so clients get qualified talent sooner and candidates get a clear, responsive process from first contact to start date.

Job Description

Be Part Of A Dynamic Team

Join a global financial services organization investing heavily in modernizing its technology and building a more data-driven operating model. This opportunity sits within a Data Strategy organization supporting capital markets and securities businesses and brings together data engineers across the U.S. and offshore teams. The group is developing a strategic cloud-based data platform designed to provide a scalable foundation for securities, pricing, reference, and additional enterprise data domains.

What s In Store For You

• Engagement: W2 only (no C2C/1099)
  
• Hybrid opportunity based in Charlotte, North Carolina.
  
• Long-term contract engagement supporting a major enterprise data transformation.
  
• Opportunity to contribute to a strategic Azure-based platform being built across multiple capital-markets data domains.
  
• Work alongside experienced data engineering, cloud, and financial technology professionals across geographically distributed teams.
  

How You Will Make An Impact

• Design and develop production-grade data engineering solutions supporting a strategic enterprise data platform.
  
• Build scalable data pipelines and processing capabilities using Python, PySpark, Azure, and Databricks.
  
• Contribute to the development of a centralized reference-data platform supporting securities and pricing information.
  
• Develop and integrate APIs using Python frameworks such as FastAPI.
  
• Implement data workflows using Azure Data Factory, Azure Data Lake Storage Gen2, Azure databases, Azure Functions, and related services.
  
• Design efficient ETL/ELT processes for structured and potentially high-volume financial datasets.
  
• Apply strong SQL expertise across relational and NoSQL data environments.
  
• Participate throughout the DevOps lifecycle, including source control, automated deployments, CI/CD, testing, and production implementation.
  
• Follow enterprise engineering and development standards while collaborating with U.S. and international technology teams.
  

Requirements

Do You Bring Proven Success in Azure Data Engineering and Python-Based Data Platforms?

• 10+ years of relevant software/data engineering experience , with significant hands-on data engineering responsibilities.
  
• Proven experience designing and implementing data solutions within Microsoft Azure .
  
• Strong hands-on development skills with Python and PySpark .
  
• Advanced experience with Azure Databricks .
  
• Experience building solutions with Azure Data Factory and Azure Data Lake Storage Gen2 .
  
• Experience working with Azure databases and cloud-based data architectures.
  
• Strong SQL skills across relational database environments; NoSQL experience is valuable.
  
• Familiarity with Azure Functions and API management/integration patterns.
  
• Strong understanding of ETL and ELT architectures and processes .
  
• Experience with modern engineering practices including Git, Jenkins, CI/CD, and DevOps workflows .
  
• Financial services experience is preferred, particularly exposure to securities, financial instruments, asset classes, reference data, pricing data, or market data.
  
• Strong collaboration and communication skills with the ability to work effectively across distributed technical teams.