Join our team as a Data Engineer, focusing on the design, development, and maintenance of robust data solutions. You will be instrumental in creating sophisticated data pipelines that manage data generation, collection, and processing.

Key responsibilities include ensuring high data quality and implementing effective ETL processes for seamless data migration and deployment across systems. This role is crucial for supporting our advanced data infrastructure and meeting critical analytics needs.

- Design, develop, and maintain comprehensive data solutions for data generation, collection, and processing. - Create efficient data pipelines to ensure smooth data flow and integration across various systems. - Implement ETL processes to extract, transform, and load data, facilitating effective migration and deployment. - Monitor and optimize data workflows to enhance performance and reliability. - Collaborate with cross-functional teams to understand data requirements and deliver scalable solutions. - Document data processes and maintain clear communication with stakeholders.

A minimum of 3 years of dedicated experience with the Databricks Unified Data Analytics Platform is essential for this role. Candidates are expected to possess strong proficiency in Databricks Unified Data Analytics Platform, Microsoft Azure Databricks, Microsoft Azure Analytics Services, and PySpark.

We require individuals who can perform independently and contribute as Subject Matter Experts (SMEs). Active participation in team discussions and proactive problem-solving are highly valued. A solid understanding of data pipeline architecture and ETL best practices is necessary, along with experience in cloud-based data platforms and distributed computing.