Drive the implementation and optimization of centralized data repositories and data lake architectures, supporting enterprise-wide analytics and reporting.
Identify, diagnose, and resolve data-related issues, ensuring data quality, integrity, and availability for downstream analytics and business applications.
Apply advanced data modeling techniques to solve real-world business challenges, ensuring data consistency, integrity, and performance.
Provide advanced support and troubleshooting for data pipelines, ETL/ELT processes, and data integration workflows across cloud and on-prem environments.
Enhance and mentor others in organizational, communication, and analytical skills, fostering a collaborative and data-driven engineering culture.
Gain exposure to the end-to-end machine learning lifecycle, from experimentation to production, by enabling robust and scalable data access for model training...