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Senior Data Engineer to join a high-performing data team responsible for building and maintaining a modular ETL framework used for financial reporting and risk systems. You will work in a modern engineering environment using Python, Apache Spark, and Azure Databricks, contributing to scalable, well-tested, and production-grade data pipelines.
Job Responsibility:
Build and maintain ETL pipelines using Python and Spark
Apply data engineering best practices and ensure high-quality code standards
Work with SQL and relational databases for data processing
Integrate pipelines within Azure DevOps CI/CD workflows
Support and interact with downstream reporting and risk systems
Participate in architectural discussions and future improvements
Ensure robust unit and integration testing
Collaborate on orchestration using Apache Airflow or Azure Durable Functions (C#)
Requirements:
5+ years of experience in Python development within data engineering
Strong experience with Apache Spark / PySpark (Databricks preferred)
Solid understanding of ETL frameworks and data processing patterns