Shape and enhance data infrastructure by designing, building, and maintaining robust data solutions. This role focuses on the generation, collection, and intricate processing of data. Key responsibilities include architecting efficient data pipelines, rigorously ensuring data integrity, and implementing effective ETL processes for seamless data migration and deployment across diverse systems. The aim is to optimize data workflows and resolve any emerging issues.

Continuous monitoring and optimization of data pipeline performance are crucial to guarantee reliability and efficiency. A significant aspect of this role involves meticulously documenting data processes and workflows to foster clarity and facilitate knowledge sharing within the team. Furthermore, providing guidance and support to junior team members is an integral part of daily operations.

- Drive data solution design, development, and maintenance to support data generation, collection, and processing. - Architect and build efficient data pipelines, ensuring seamless data migration and deployment across systems. - Implement robust ETL processes and maintain high standards of data quality. - Collaborate with cross-functional teams to understand data needs and deliver scalable solutions. - Monitor and optimize data pipeline performance for optimal reliability and efficiency. - Document data processes and workflows for knowledge sharing and clarity. - Mentor and support junior team members, contributing to their professional growth.

- Proven expertise in designing, developing, and maintaining data generation, collection, and processing solutions. - Strong proficiency in creating data pipelines and ensuring data quality. - Extensive experience in implementing ETL (extract, transform, load) processes for data migration and deployment. - Minimum of 3 years of dedicated experience with AWS Glue. - Familiarity with cloud-based data integration and ETL tools. - Solid understanding of data pipeline architecture and data warehousing concepts. - Demonstrated ability to troubleshoot and resolve data processing issues effectively. - Experience with scripting languages for automation and data manipulation. - Knowledge of data governance and security best practices. - Must have completed 15 years of full-time education.