Head of Data, Platform and Intelligence

Role Overview

• Define the North Star Data Architecture
• Establish and evolve the target-state data architecture, aligning storage, compute, search, and access patterns into a unified platform
• Drive architectural clarity across warehouse, search, object storage, and real-time systems
• Ensure consistency in schemas, metadata, and governance frameworks across all data domains
• Build an AI-Native Data Foundation
• Design a data platform optimized for AI and agentic workloads, including: API-first, agent-callable data services
• Hybrid retrieval patterns (search + analytical + vector)
• Real-time and batch data unification
• Enable scalable support for LLMs, RAG pipelines, and intelligence workflows
• Own Data as a Product
• Establish a data-as-a-product operating model, enabling discoverable, reusable, and well-governed data assets
• Define and standardize data contracts, ownership models, and domain boundaries
• Translate platform capabilities into customer-facing data products and differentiators
• Lead Platform Rationalization and Evolution
• Rationalize and evolve the current ecosystem into a cohesive and cost-efficient architecture
• Lead phased, low-risk migrations and consolidations aligned to business priorities
• Balance short-term pragmatism with long-term architectural integrity
• Own Performance, Reliability, and Cost Economics
• Accountable for performance, scalability, and reliability of all data systems
• Establish clear unit economics for data (e.g., cost per query, cost per workload, storage efficiency)
• Implement strong observability, SLOs, and incident management practices

Requirements

• 10+ years of experience in data platforms, data engineering, or distributed systems
• Strong background working within multi-cloud or hybrid environments, including hands-on experience with Google Cloud Platform (GCP)
• Proven experience designing and evolving large-scale data platforms through major architectural transitions (e.g., warehouse, search, Lakehouse, or multi-cloud transformations)
• Deep expertise across multiple data paradigms, including:
• Analytical warehouses
• Search/index systems
• Object storage and distributed data systems
• Experience building platforms that support AI, ML, or agent-driven systems
• Familiarity with vector search, retrieval architectures, and modern AI data patterns
• Experience with graph-based data models, entity resolution, or knowledge graphs
• Strong communication skills and the ability to collaborate effectively across technical and non-technical teams.
• Experience operating in regulated, high-stakes, or mission-critical environments is strongly preferred.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field required. Master’s degree or PhD preferred.

Tech Stack

• Cloud
• Distributed Systems
• Google Cloud Platform