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Tier-1 employer and Bengaluru metro increase density, but senior specialized role reduces applicant pool.
Deep GCP data platform, governance, and MLOps expertise required, making cross-industry transfers difficult.
Explicit 15+ years, mandated GCP mastery, specific tech stack and leadership responsibilities make filters very strict.
Architect and deliver enterprise-scale, petabyte-scale data platforms on Google Cloud Platform with defined SLOs for freshness, availability, and reliability.
Lead architectural governance and innovation initiatives across data engineering teams including adoption of AI/LLM technologies and domain-oriented architectures like data mesh.
Mentor and lead multiple engineering communities, driving technical hiring strategy, standards, and cross-functional stakeholder management including executive presentations and external representation.
15+ years of data engineering experience with 8+ years specifically on Google Cloud Platform.
Master's or bachelor's degree in computer science, engineering, or related field; Master's degree strongly preferred.
Expertise in Google Cloud Platform services including BigQuery, Cloud Dataflow, Pub/Sub, and Vertex AI.
Proven experience leading delivery of large-scale, complex data platform initiatives with data governance and security compliance (GDPR, SOX).
Senior-level data engineer or architect with a strong track record of enterprise-scale system design and delivery on GCP.
Strategic and technical leadership experience managing cross-functional teams and driving adoption of modern data architectures and AI/ML integrations.
Experienced in balancing architecture trade-offs for scalability, cost, performance, and security with influence at executive and organizational levels.