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Tier-1 brand, mid-level generalist data role, metro location, and broad tech list drive high competition.
Core data engineering skills are transferable across industries, though banking compliance experience moderately increases sensitivity.
Explicit 4+ years, specific data stack expectations, and regulated banking environment make shortlisting highly strict.
Lead moderately complex technical initiatives including design, coding, testing, and deployment within the technology domain.
Collaborate with peers and mid-level managers to resolve technical challenges and lead a team to meet client needs.
Contribute to large-scale strategy planning and modernization of applications away from legacy tech stacks, ensuring high code quality and engineering standards.
4+ years of software engineering experience or equivalent.
Hands-on experience with Python, Spark, Iceberg, and Hive is required.
Experience in SQL development and tuning, and supporting large enterprise-scale data environments.
Work Experience Required: 4+ years. Notice period: Not explicitly mentioned in the JD.
Experienced in modern data platforms with expertise in data lakes, lakehouse architectures, and cloud-native/open-table formats.
Familiar with GenAI, Agentic AI, LLM adoption, and integration of AI into data engineering workflows.
Able to operate effectively in fast-paced Agile environments with cross-functional collaboration and a focus on innovation and automation.