This role focuses on designing, developing, and maintaining robust data solutions for data generation, collection, and processing. You will be instrumental in creating efficient data pipelines, ensuring high data quality, and implementing ETL processes for seamless data migration and deployment across systems.

Key responsibilities include becoming a subject matter expert, actively contributing to team discussions, and providing effective solutions to technical challenges. Collaboration with cross-functional teams is essential to understand data requirements and deliver scalable solutions. The position also involves monitoring and optimizing data workflows for enhanced performance and reliability, along with documenting processes and maintaining clear team communication.

The ideal candidate will have a strong background in data engineering principles and a proven ability to troubleshoot and resolve data quality issues. Understanding of data governance and security best practices is also expected. This is an exciting opportunity to contribute to critical data infrastructure and support organizational data needs.

- Design, develop, and maintain data generation, collection, and processing solutions. - Create and manage efficient data pipelines. - Ensure data integrity and quality throughout the data lifecycle. - Implement ETL processes for data migration and deployment. - Actively participate in team discussions and problem-solving. - Collaborate with cross-functional teams to deliver scalable data solutions. - Monitor and optimize data workflows for performance and reliability. - Document data processes and maintain team communication. - Provide guidance and support to junior team members.

- Minimum 3 years of experience, specifically with the Databricks Unified Data Analytics Platform. - Demonstrated experience in building and managing scalable data pipelines and ETL processes. - Strong understanding of data integration, transformation, and migration techniques. - Familiarity with cloud-based data platforms and distributed computing frameworks. - Proficiency in troubleshooting and resolving data quality and pipeline issues. - Knowledge of data governance and security best practices. - A foundational education of 15 years of full-time study is required.