Senior Azure Data Engineer - Python, PySpark & Databricks 3668442
Axiom Path
Job Description
Job Description
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.
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...buildingOur team runs a range of data and AI projects across the... ...hybrid role that spans data engineering, AI product enablement, and platform... ...Data Lake architecture using Python, Spark, SQL, and modern ETL... ...(e.g., Snowflake, Databricks, Delta Lake) alongside distributed...DatabricksSeniorFull timeWork at officeFlexible hoursDay shift- ...Cloud Data EngineerThis position is for a Cloud Data engineer with a background in Python, Pyspark, SQL and data warehousing for enterprise level systems. The position calls... ...Design, develop, and deploy Spark program in DataBricks environment to process and analyze large...Databricks
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