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Tier-1 brand, metro location, and broad enterprise data skillset increase candidate competition density.
High because deep enterprise data, GCP specialization, and governance needs limit industry transferability.
Very high due to explicit 15+ years, 8+ years GCP, and extensive mandatory tech and governance requirements.
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Architect and lead the delivery of petabyte-scale, cloud-native data platforms on Google Cloud with measurable service level objectives for freshness, availability, and reliability.
Drive organizational adoption of domain-oriented data architecture (e.g., data mesh), AI/LLM integration, and engineering best practices including performance, cost governance, and reliability.
Mentor data engineering teams across org-wide initiatives, lead architectural governance, and represent technical strategy to executive leadership and external forums.
15+ years of data engineering experience, with 8+ years specifically on Google Cloud Platform (GCP).
Master's or Bachelor's degree in Computer Science, Engineering, or related field (Master's strongly preferred).
Expertise in BigQuery, Dataflow, Pub/Sub, Apache Beam, Apache Spark, Terraform, Python/Java, and distributed systems design.
Experience with data governance, compliance frameworks (GDPR, SOX), security architecture, and cost/performance optimization at enterprise scale.
Senior technical leader with proven ability to lead global, complex data platform initiatives end-to-end.
Strong architectural thinker who balances scalability, performance, security, and cost while connecting technical decisions to business outcomes.
Experienced in leading change at scale by influencing cross-functional teams, adopting AI/ML innovations (Agentic AI, Model Context Protocol), and fostering engineering excellence.