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Tier-1 employer, mid-level generalist role, metro office and broad skillset drive high candidate density.
Data platform skills are transferable but banking controls, compliance, and domain specifics increase sensitivity.
Explicit 3+ years plus mandatory stack (Java, Spark, Scala, AWS, SQL) increases filter rigidity.
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Lead and oversee data strategy, governance, risk management, reporting, and analytics across multiple business functions.
Design, develop, test, deploy, and maintain scalable applications leveraging Java, Python, Scala, Spark, and cloud technologies, focusing on big data and data platform engineering.
Integrate and manage AI-assisted development tools for coding, testing, and automation, ensuring responsible and secure AI practices.
3+ years of applied software engineering experience with formal training or certification.
Expert-level skills in Java, AWS, databases, Python, Scala, Spark, Ab Initio or Informatica, and complex SQL development.
Experience in big data, data warehousing (including star schema), data analytics, and cloud deployment (AWS/Azure/GCP).
Proven hands-on experience using enterprise-authorized AI-assisted software development tools and understanding of responsible AI use in engineering workflows.
Experienced in delivering data and analytics projects with expertise in data platform engineering, batch and streaming data processing.
Able to evaluate and implement advanced AI technologies within software development life cycles, maintaining security and compliance.
Capable of rapid technology adoption and process improvement within collaborative agile teams, with knowledge of controls and compliance in data applications.