Senior Azure Data Engineer Python, PySpark & Databricks

Axiom Path•Charlotte, NC
•Hybrid

About The Position

Join a global financial services organization that is heavily investing in modernizing its technology and building a more data-driven operating model. This opportunity is within a Data Strategy organization supporting capital markets and securities businesses, bringing together data engineers across 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.

Requirements

  • 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.
  • Experience designing or developing REST APIs using FastAPI or comparable Python frameworks.
  • 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.
  • Strong collaboration and communication skills with the ability to work effectively across distributed technical teams.

Nice To Haves

  • Financial services experience is preferred, particularly exposure to securities, financial instruments, asset classes, reference data, pricing data, or market data.

Responsibilities

  • 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.
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