Senior Azure Data Engineer – Python, PySpark & Databricks 3668442 (Charlotte, NC)
Summary
Long-term W2 contract (via Axiom Path) for a Senior Azure Data Engineer, hybrid in Charlotte, NC, building a strategic Azure cloud data platform for a global financial services organization's capital markets and securities data. Daily work centers on Python, PySpark, and Databricks pipelines plus Azure Data Factory, ADLS Gen2, FastAPI services, and CI/CD.
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.
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.
- 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.
- 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.