Join our team as a Data Platform Engineer, contributing to the design and architecture of our data platform. You will collaborate with integration and data architects to ensure seamless system and data model integration.

This role involves developing and optimizing analytics solutions on the Microsoft Azure platform, acting as a senior contributor. Your focus will be on translating business needs into scalable and reliable analytics, building data pipelines, crafting transformation logic, and maintaining data quality.

- Design and develop data ingestion pipelines utilizing Azure Data Factory. - Build and manage data storage and analytics layers with Azure Data Lake Storage and Azure Synapse Analytics. - Develop and optimize data transformations using PySpark, Spark SQL, and SQL. - Implement structured data modeling for curated datasets. - Support Power BI dataset development and performance tuning. - Perform data validation and reconciliation to ensure accuracy and consistency. - Troubleshoot and resolve data pipeline and performance issues. - Contribute to code reviews, documentation, and knowledge sharing.

We are seeking a professional with 3 to 5 years of experience in data engineering, BI, or analytics. A strong foundation in Microsoft Azure Analytics services is essential, including hands-on experience with Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake Storage Gen2.

Proficiency in PySpark or Spark SQL for data processing, along with a solid understanding of data warehousing concepts and SQL for querying and transformations, is required. Familiarity with Power BI datasets and data ingestion patterns is also expected.