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Strong Tier-1 brand and broad cross-functional data-cloud skillset increase candidate density.
Core data engineering and cloud skills are transferable, though consulting/AI experience is preferred.
Explicit 8–12 years and 3+ years management plus many mandatory cloud/data technologies enforce strict filtering.
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Own end-to-end cloud-native data platform architecture, delivery, reliability, and cost-efficiency for analytics and AI use cases.
Translate business needs into scalable cloud data architectures including ingestion, processing, storage, APIs, and front-end UI.
Manage and mentor engineering teams, drive program delivery, enforce best practices, and maintain stakeholder communication including status, risks, and roadmap alignment.
8-12+ years in software/data engineering and cloud platform roles with at least 3 years managing engineering teams.
Experience designing and operating cloud-native data platforms on AWS, Azure, or GCP.
Strong full-stack development skills (backend: Python/Java/Scala/Go; frontend UI experience is a plus).
B Tech/M Tech in Computer Science or related fields like Statistics/Econometrics/Economics from reputed institutes.
Experienced leader capable of managing multiple engineering pods and driving cloud data platform modernization including migration initiatives.
Strong cross-functional collaborator comfortable with stakeholder management, program delivery, and vendor evaluation.
Technically proficient in modern data engineering stack including Spark, Databricks, lakehouses, feature stores, container orchestration, and infrastructure as code.