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Tier-1 bank, mid-level data role in Bangalore with common 5+ years skillset; high applicant density.
Medium: core data engineering skills transferable, but financial analytics preference increases domain specificity.
High due to explicit 5+ years and many mandatory cloud, Spark, and IaC skills.
Design, build, and maintain production-grade ETL/data pipelines using PySpark, AWS Glue, and Apache Iceberg.
Develop and operate backend microservices and APIs using Java Spring Boot and Python.
Build and manage infrastructure-as-code and CI/CD pipelines; optimize data workflows for performance, cost, and reliability; mentor junior engineers and lead use of AI-assisted development tools.
Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).
5+ years of professional software engineering experience.
Proficiency in Java or Python, software design fundamentals, and AWS cloud services (S3, Glue, Lambda, IAM, RDS/Aurora).
Experience building data pipelines, working with SQL and relational databases, distributed data processing (Spark), Git-based workflows, CI/CD practices, and leading AI-assisted software development tools use.
Experienced in large-scale analytics or financial/revenue data domains with strong backend and data engineering skills.
Operates at senior engineer level with leadership in AI-assisted development tool adoption, testing discipline, and secure, compliant engineering practices.
Comfortable managing infrastructure-as-code and optimizing complex data workflows for production, including mentor responsibilities.