Be Part Of A High-Performing Team
Join a global financial services technology organization advancing a major digital transformation across its capital markets and securities businesses. The Data Strategy team is modernizing how enterprise data is managed, governed, and delivered through a strategic cloud-based data platform. This role will collaborate with engineering teams across the U.S. and India to build scalable data capabilities supporting securities, pricing, reference data, and additional capital markets domains.
What’s In Store For You
- Engagement: W2 only (no C2C/1099)
- Hybrid opportunity based in Charlotte, North Carolina.
- Work on a long-term strategic data transformation initiative supporting capital markets technology.
- Gain exposure to enterprise-scale Azure architecture, modern data engineering, and financial-market datasets.
- Collaborate with geographically distributed engineering and business teams.
How You Will Make An Impact
- Design, develop, and enhance a strategic enterprise data platform hosted within Microsoft Azure.
- Build scalable data pipelines and processing solutions using Python, PySpark, Azure Data Factory, and Databricks.
- Support the development of a reference-data platform covering securities and pricing information before expanding into additional data domains.
- Develop ETL/ELT solutions that ingest, transform, validate, and distribute complex financial datasets.
- Build and integrate REST APIs using Python frameworks such as FastAPI.
- Develop cloud-native functionality using Azure Functions, API management capabilities, databases, and Azure Data Lake Storage Gen2.
- Apply established development standards, source-control practices, and CI/CD processes across the engineering lifecycle.
- Partner closely with technology and data teams across multiple regions to deliver reliable and maintainable data solutions.
Do You Bring Proven Success in Azure Data Engineering and Python Development?
- Extensive professional data engineering experience, with the role targeting a highly experienced engineer capable of operating independently in an enterprise environment.
- Strong hands-on development expertise with Python and PySpark.
- Proven experience designing and implementing data solutions in Microsoft Azure.
- Hands-on experience with Azure Data Factory and Azure Data Lake Storage Gen2.
- Strong working knowledge of Azure Databricks.
- Experience with Azure databases, Azure Functions, API management, and modern Microsoft data-platform capabilities.
- Advanced SQL skills across relational and/or NoSQL database environments.
- Experience developing APIs using FastAPI or comparable Python frameworks.
- Strong understanding of ETL and ELT architecture and processing patterns.
- Familiarity with Git-based development, Jenkins or comparable CI/CD tooling, and modern DevOps practices.
- Ability to collaborate effectively with distributed technical teams while following enterprise engineering standards.
- Financial services experience involving financial instruments, asset classes, securities, pricing, or market data is highly valuable.
