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Tier-1 brand, Bangalore metro, and broad cross-functional data requirements increase competition.
Data engineering leadership skills transfer across industries, but cybersecurity enterprise context favors domain-experienced candidates.
Requires proven senior data engineering leadership, cross-functional domain expertise, and hands-on technical ownership.
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Lead a global team across data engineering, analytics, and product management to deliver high-impact data initiatives supporting business domains like People, Finance, GTM, Support, and Marketing.
Integrate and oversee data engineering, reporting, insights, analytics, and machine learning functions, ensuring technical coherence across the data lifecycle.
Partner with US leadership and business stakeholders to drive project ownership from inception through execution and deliver strategic insights to executive audiences.
Proven experience building, scaling, and managing high-performing technical teams in data engineering and analytics.
Deep technical expertise across data engineering pipelines, database management, advanced analytics, and machine learning.
Demonstrated success collaborating across global, cross-functional teams and working with business stakeholders in domains such as Finance, People, Marketing, Support, and GTM.
Work Experience Required: Not explicitly mentioned in the JD; Immigration sponsorship not available (no work visa sponsorship).
Experienced leader with a hands-on 'builder' mindset who actively engages in technical details rather than purely managing resources or programs.
Strong ability to operate across multiple time zones and cultures, especially bridging US and India teams in a global data organization.
Effective at translating complex technical work into strategic insights for executive-level communication and decision-making.