Senior Azure Data Engineer Python, PySpark & Databricks

Axiom Path • Charlotte, NC

1d • Hybrid

About The Position

Join a global financial services organization investing in technology modernization and a data-driven operating model. This role is part of a Data Strategy organization supporting capital markets and securities businesses, working with U.S. and offshore teams to develop a strategic cloud-based data platform for securities, pricing, reference, and other enterprise data domains.

Design and develop production-grade data engineering solutions for the enterprise data platform. Build scalable pipelines using Python, PySpark, Azure, and Databricks; contribute to a centralized reference-data platform; and develop APIs with Python frameworks such as FastAPI. Implement workflows using Azure Data Factory, Azure Data Lake Storage Gen2, Azure databases, Azure Functions, and related services. The role also involves designing ETL/ELT processes, applying SQL across relational and NoSQL environments, and participating in the DevOps lifecycle from source control and testing through CI/CD and production implementation.

This is a long-term W2 contract engagement (no C2C/1099) with a hybrid arrangement based in Charlotte, North Carolina. The engineer will collaborate with distributed U.S. and international teams and follow enterprise engineering and development standards.

Requirements

• 10+ years of relevant software or data engineering experience, with significant hands-on data engineering responsibilities.
• Proven experience designing and implementing data solutions in 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.
• Experience designing or developing REST APIs using FastAPI or comparable Python frameworks.
• Familiarity with Azure Functions and API management or 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

• NoSQL experience.
• Financial services experience, 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 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 SQL across relational and NoSQL data environments.
• Participate in 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed