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Tier-1 brand, mid-level data role, metro location, and broad skills increase candidate competition.
Core data engineering skills are transferable across industries but banking domain expectations raise sensitivity.
Explicit 3+ years, certification requirement, and mandatory Java/cloud/databricks skills enforce strict filtering.
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Design, develop, and maintain secure, scalable software solutions focused on data engineering using Java, Spark, and Databricks.
Leverage AI-assisted software development tools to improve code quality, delivery speed, and system architecture while ensuring correctness and security.
Analyze and visualize large, complex data sets to identify patterns for continuous improvement of code hygiene and architecture.
3+ years of applied software engineering experience with formal training or certification.
Hands-on experience with Java (Spring, Spring Boot), database design, data modeling, and SQL querying.
Experience with at least one cloud platform: AWS, GCP, or Azure.
Experience as a data engineer working with large complex data using enterprise tools and using enterprise-authorized AI-assisted development tools.
Seasoned engineer capable of working on complex system design, development, and operational stability in large corporate environments.
Experienced in enterprise-grade AI-assisted development workflows, including validating AI outputs and applying responsible AI practices.
Strong background in data engineering technologies such as Apache Spark, Databricks, and data lake architectures with exposure to cloud environments.