Responsibilities Design and develop the robust data solutions
on SQL Server, ensuring optimal performance through advanced query optimization, indexing strategies, and partition management Design and optimize large-scale ETL pipelines
using Apache Spark to process high-volume data from diverse sources across the bank Ensure data quality and reliability
across the platform through comprehensive validation frameworks and proactive monitoring Collaborate with analytics teams
using SAP BusinessObjects and other systems to deliver regulatory reports and business intelligence Drive continuous improvement
by evaluating and adopting emerging technologies and best practices in big data engineering Troubleshoot and resolve
complex data pipeline issues, performance bottlenecks, and system failures Requirements Around 8 years of data engineering experience
, preferably in financial services or high-volume data environments Advanced SQL Server
expertise including: Query opti...