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Tier-1 brand, popular mid-level data role, metro location, and broad Spark/AWS skillset increase applicant density.
Core data engineering skills are broadly transferable, though enterprise banking domain knowledge gives moderate bias.
Mandatory 3+ years and expert Spark/AWS/Java/Python requirements make filtering stringent.
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Design, develop, and maintain secure, scalable software solutions using Java, AWS, Python, Spark/PySpark, and database technologies.
Produce architecture and design artifacts for complex applications ensuring compliance with design constraints.
Analyze large, diverse data sets to identify issues and drive improvements in coding hygiene and system architecture.
3+ years of practical software engineering experience with formal training or certification.
Expert proficiency in Java, AWS, Python, Spark/PySpark, and database querying in enterprise environments.
Strong experience across full SDLC within an Agile framework including CI/CD and application security.
Hands-on experience using enterprise-authorized AI-assisted development tools with ability to validate and refine AI-generated outputs.
Experienced in designing and maintaining complex, enterprise-grade software systems with operational stability.
Skilled in leveraging cloud technologies and knowledge of software engineering across domains including AI/ML and mobile.
Proficient in integrating AI-assisted tools responsibly within engineering workflows, ensuring security and data sensitivity compliance.