10+ years of software development and data engineering experience preferred
Strong proficiency in Python and PySpark for production-grade applications
Proven experience with Microsoft Azure data solutions
Hands-on expertise with Azure Databricks, Azure Data Factory, and Azure Data Lake Storage Gen2
Strong SQL development skills for relational and NoSQL databases
Experience developing RESTful APIs using FastAPI or similar frameworks
Familiarity with Git, Jenkins, and DevOps practices
Responsibilities
Design and enhance scalable data pipelines in an Azure cloud environment
Build and maintain ETL/ELT workflows using Python and Azure tools
Contribute to a centralized data platform focusing on securities reference data
Develop Python-based APIs for data exchange between applications
Implement data ingestion and processing solutions using Azure technologies
Write and optimize SQL queries for data integration
Participate in CI/CD processes and collaborate with engineering teams
Benefits
Opportunity to work with cutting-edge Azure technologies
Collaborative environment with cross-functional teams
Focus on developing scalable and maintainable data solutions
Engagement in continuous improvement of data platform performance
Exposure to financial services and capital markets data
Full Job Description
Job Description How You Will Make An Impact
Design, develop, and enhance scalable data pipelines and integration solutions within an enterprise Azure cloud environment.
Build and maintain ETL/ELT workflows using Python, PySpark, Azure Data Factory, and Azure Databricks.
Contribute to the development of 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 to support 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 while helping improve the performance, quality, and reliability of the data platform.
Requirements Do You Bring Proven Success in Azure Data Engineering and Python-Based Data Integration?
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.
Experience with Microsoft Fabric or comparable Azure data platform technologies is beneficial.
Financial services experience, particularly involving capital markets, securities, financial instruments, asset classes, or market data, is advantageous.
Strong troubleshooting, analytical, and communication skills, with the ability to collaborate effectively across distributed technical teams.
