Primary Responsibilities

• Design and implement scalable, performance-driven data storage systems using Azure services.
• Develop ETL processes using Azure Data Factory to extract, transform, and load data into data warehouses or lakes.
• Utilize Apache Spark for big data processing and create data workflows to support analytics and machine learning.
• Build and maintain applications in preparation for large-scale architectural migration within an Agile environment.
• Monitor and optimize data pipelines and database performance for efficiency.
• Document data engineering processes, data models, and pipelines for transparency and maintainability.

Qualifications

• 5+ years of experience in data engineering and analytics platforms on Azure.
• Proficiency in Azure SQL Database, Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake.
• Strong knowledge of data integration, ETL tools (SSIS, Power BI Dataflow), and database management (MSSQL).
• Experience with cloud-based data migration and big data technologies like Apache Spark.
• 3+ years of programming experience in Python/PySpark.
• Strong analytical, problem-solving, and troubleshooting skills.
• Familiarity with Agile methodologies and tools such as Jira, Confluence, and DevOps.

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