Join our dynamic team as a Senior Azure Data Engineer, focusing on data modernization and migration projects. This role offers the opportunity to design, develop, and maintain robust, scalable data solutions leveraging cutting-edge Azure services and Databricks.

We are looking for a skilled professional with a strong foundation in data engineering best practices. You will play a key role in optimizing data workflows, ensuring data integrity, and making data readily available for advanced analytics and business intelligence initiatives.

Key responsibilities include designing, developing, and deploying scalable data pipelines using Databricks (PySpark, Spark SQL) and Azure Data Factory. You will implement ETL/ELT processes to ingest, transform, and load data into data lakes and warehouses, while optimizing performance and scalability. Additionally, you'll write and optimize complex SQL queries, utilize PySpark for large-scale data processing, and implement efficient data partitioning strategies. Integrating data from diverse sources, including APIs and streaming data, is crucial. You will also ensure data quality, consistency, and security through robust data governance practices, collaborate with stakeholders, and document all data pipelines and architecture.

To excel in this role, you need 5 to 9 years of experience in data engineering, with a specific focus on Azure and Databricks. Essential skills include hands-on experience with Databricks (including Unity Catalog, Lakehouse, Medallion Architecture), Azure Data Factory, Azure Data Lake Storage, and Azure SQL Database. Strong expertise in SQL for complex query writing and optimization, along with PySpark for data processing, is required. A solid understanding of ETL/ELT processes, data modeling techniques, and data governance practices is also vital. A Bachelor's or Master's degree in Computer Science, Information Technology, or a related field is preferred. Relevant certifications are a plus.