Head of Data

Our client is a fast-growing, AI-first enterprise software company. Its planning platform helps some of the world’s largest brands make faster, smarter decisions. It brings planning work that usually sits in separate silos onto one platform, which cuts waste and recovers value that large enterprises lose to inefficiency. The company is well funded, operates globally and has a strong record of growth.

Remote (US)

The company is looking for an exceptional technology executive to define and build the next generation of its enterprise data platform. This is one of the most senior engineering leadership roles in the company. It covers data strategy, platform architecture, distributed systems engineering, intelligent data integration, reusable data products, and the infrastructure that connects enterprise data to the platform’s core capabilities.

This is not a traditional Chief Data Officer role focused on internal analytics, reporting or administrative governance. The company wants a hands‑on builder: an executive who can design large-scale data systems from first principles, lead a high-performing engineering organization, turn recurring customer integration problems into reusable platform capabilities, and hold credible conversations with senior technology executives at Fortune 500 companies.

Build an AI-native enterprise data foundation that makes data faster to onboard, easier to trust, grounded in business meaning, reusable across solutions and efficient to run at scale.

• Data Platform Architecture:
  Own the technical direction and long-term evolution of the company’s data platform across ingestion, storage, streaming, transformation, schema management, metadata services, APIs, caching and large-scale query processing.
• AI-Native Data Integration:
  Drive the technology and products that make enterprise data integration faster and more reliable. Design production systems that use AI and automation to inspect source schemas, resolve entity relationships, detect quality issues, generate transformations and adapt as data environments change.
• Reusable Data Products:
  Build reusable data assets that scale across deployments, including standard connectors, canonical datasets, master data capabilities, lineage and provenance frameworks, and unified developer interfaces.
• Semantic & Business Meaning:
  Work closely with platform and application engineering teams to connect raw enterprise data to complex business logic, domain models, operating constraints and decision engines.
• Product & Commercial Impact:
  Drive platform capabilities that speed up customer onboarding, reduce deployment friction and shorten the path from raw customer data to a working capability. Work directly with Product, Engineering, Field Engineering, Sales, partners and enterprise clients.
• Organizational Leadership:
  Recruit, develop and scale an exceptional engineering organization across data engineering, platform infrastructure and integration. Hold the team to demanding technical standards and build a culture of first-principles problem-solving.
• AI-Native Engineering Leadership:
  Personally use and champion modern AI-assisted development tools and coding environments to speed up codebase exploration, prototyping, testing and technical execution, while keeping close technical oversight.

• Experience:
  
  15+ years of software and data engineering leadership experience, with a proven record of building and scaling complex, enterprise-grade data platforms.
• Education:
  
  A bachelor’s degree in Computer Science, Machine Learning, Statistics or a related quantitative field.
• Technical Depth:
  Deep engineering strength in databases, distributed systems, streaming architectures, metadata…