Senior Azure Data Engineer – Python/PySpark & Databricks

Axiom Path • Jersey City, NJ

13h • Hybrid

About The Position

Join a leading global financial services organization investing in the modernization of its enterprise data infrastructure. The technology team supports capital markets operations, including securities trading, financial instruments, and market data management. As part of a digital transformation initiative, the Data Strategy team is developing a cloud-based data platform to improve how critical financial information is collected, processed, integrated, and distributed.

In this role, you will collaborate with engineering teams across the United States and internationally to build scalable data solutions using modern Azure technologies. The work includes developing data pipelines and integration solutions, initially focused on securities reference data and pricing information, and contributing to an enterprise-scale data platform. The position is a long-term W2 contract, based in Jersey City, NJ, with a hybrid work arrangement.

Requirements

• 10+ years of relevant software development and data engineering experience preferred, with substantial hands-on experience building enterprise data solutions.
• Strong proficiency in Python and PySpark, including developing production-grade data processing and integration applications.
• Proven experience developing data solutions within Microsoft Azure.
• Hands-on expertise with Azure Databricks, Azure Data Factory, and Azure Data Lake Storage Gen2.
• Experience working with Azure databases, Azure Functions, and API management technologies.
• Strong SQL development skills, including experience with relational and/or NoSQL databases.
• Practical experience developing RESTful APIs using FastAPI or comparable Python frameworks.
• Strong understanding of ETL/ELT architecture, data ingestion, transformation, and integration patterns.
• Familiarity with Git, Jenkins or similar tools, automated deployment pipelines, and DevOps practices.
• Strong troubleshooting, analytical, and communication skills, with the ability to collaborate effectively across distributed technical teams.

Nice To Haves

• Experience with Microsoft Fabric or comparable Azure data platform technologies.
• Financial services experience, particularly involving capital markets, securities, financial instruments, asset classes, or market data.

Responsibilities

• Design, develop, and enhance scalable data pipelines and integration solutions in an enterprise Azure cloud environment.
• Build and maintain ETL/ELT workflows using Python, PySpark, Azure Data Factory, and Azure Databricks.
• Contribute to a centralized data platform, initially focusing on securities reference data and pricing information before expanding into additional data domains.
• Develop Python-based APIs and serverless services to enable data exchange between enterprise applications and cloud data platforms.
• Implement data ingestion, transformation, storage, and processing solutions using Azure Data Lake Storage Gen2 and Azure database technologies.
• Write and optimize SQL queries for data processing, validation, and integration across relational and NoSQL databases.
• Participate in CI/CD processes, version control, code reviews, testing, and production deployments.
• Partner with cross-functional engineering teams to deliver reliable, maintainable, and scalable data services.
• Follow enterprise development standards and help improve data-platform performance, quality, and reliability.

What This Job Offers

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