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Tier-1 brand, mid-level generalist data role in a metro with broad skill requirements increases competition.
Core data engineering skills are transferable, though banking context adds some domain specificity.
Explicit 6+ years requirement plus mandatory Python, advanced SQL, ETL and orchestration skills make filters strict.
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Design, develop, and deploy scalable batch and real-time ETL/ELT data pipelines and transformation processes.
Implement automated data quality validation checks and monitoring to ensure accuracy, completeness, and pipeline reliability.
Optimize SQL queries, database indexing, and pipeline performance; collaborate with analytics and business teams to deliver structured datasets.
5+ years of professional experience in data engineering, database development, or related software engineering roles.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related technical field.
Strong proficiency in Python programming and advanced SQL skills.
Hands-on experience with ETL/ELT frameworks, workflow orchestration tools, and relational (PostgreSQL, MySQL) and NoSQL databases.
Experienced in building and maintaining production-grade data pipelines with a track record of delivery.
Capable of independently managing end-to-end data pipeline design, development, performance tuning, and operational monitoring.
Able to collaborate effectively with cross-functional teams including analytics, product, and business stakeholders to meet enterprise data needs.