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Strong Tier-1 brand, metro location and common data-engineer title increase applicant competition.
Technical data engineering skills are transferable, but banking domain knowledge raises fit sensitivity to medium.
Explicit 10+ years requirement plus mandatory data engineering stack and DevOps skills increases screening strictness.
Design, develop, and support data engineering applications including large-scale ETL/ELT pipelines using Python, SQL, Shell scripting, and PySpark.
Contribute to technical strategy, architecture, and ensure delivery quality with minimal production issues within a financial services context.
Lead and mentor engineering team members, drive hiring, and establish governance and risk management practices aligned with regulatory standards.
Bachelor's or Master's degree in Computer Science, Data Engineering, or related technical field.
10+ years of experience in data engineering with strong Python, Python-spark, shell scripting, and SQL skills.
Proficiency in building large-scale ETL/ELT pipelines and query optimization.
Work Location: Bangalore, India; Employment Type: Permanent; Office Working.
Experienced in financial services or familiar with financial market instruments and regulatory environments.
Skilled in modern data stack including Big Data tools (Hive, Spark, HDFS) and orchestration tools (Airflow, Control-M).
Capable of driving technical strategy, team leadership, and operational excellence in a regulated banking environment.