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Tier-1 brand plus metro locations and desirable senior data skills increase competition.
Core data engineering skills are transferable, but banking governance and domain knowledge increase sensitivity.
Role demands senior leadership plus specific Spark/Kafka/cloud and governance expertise, creating strict technical filters.
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Lead and coordinate large-scale, complex data engineering projects delivering scalable, robust data platforms and pipelines that drive business outcomes.
Define and standardize domain-wide data engineering architecture, roadmaps, and best practices focused on scalability, automation, resilience, and data quality.
Influence enterprise data strategy, drive platform modernization, and lead adoption of AI-based intelligent tooling to enhance engineering productivity and data insights.
Significant experience in data engineering, large-scale data architecture, and platform design, including leadership of data engineering teams.
Expertise with modern data technologies such as Spark, Kafka, and cloud platforms (AWS or GCP).
Experience embedding data governance, quality, and lineage practices in complex environments.
Work Experience Required: Not explicitly mentioned in the JD
Experienced senior-level technical leader capable of working across multiple teams in a matrix environment and liaising with senior stakeholders.
Strong background in distributed data processing and scalable API design for data services.
Proven ability to translate business/product requirements into scalable, secure, and high-performing technical data solutions.