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Tier-1 bank, mid-level generalist title, metro location, and broad skill set heighten competition.
Strong data and compliance requirements reduce cross-industry portability despite transferable engineering skills.
Explicit 4+ years plus mandatory Spark, Python, database, and orchestration skills increase filter strictness.
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Lead and deliver moderately complex software engineering initiatives within technical domains, including design, coding, testing, debugging, and documentation.
Collaborate with peers and mid-level managers to resolve technical challenges and lead teams to meet client needs using knowledge of policies and compliance.
Act as a project lead and escalation point, providing guidance to less experienced staff and contributing to large-scale strategic planning.
4+ years of software engineering experience, or equivalent through experience, training, military service, or education.
Must have hands-on experience with Python and Spark, including Iceberg and Hive technologies.
Experience with at least one of these databases: Oracle, MS SQL, Teradata.
Experience with at least one orchestration tool: Autosys or Airflow.
Experienced in supporting and optimizing large enterprise-scale data environments using modern Data Warehousing, Data Lakes, and Lakehouse architectures.
Demonstrated ability to monitor, tune, and troubleshoot large-scale distributed systems ensuring system reliability and scalability.
Some experience with GenAI, Agentic AI, or LLM adoption, such as utilizing Copilot or GitHub Copilot tools.