We are seeking a Director of Product & Engineering to lead ourData & AI Platforms portfolio, owning end-to-end strategy, architecture, roadmap, and execution for a modern, scalable, and AI-enabled data ecosystem.

This leader will transform fragmented data and technology capabilities into aunified, global platformthat enables analytics, automation, AI-powered workflows, and ecosystem integration. You will lead Engineering teams and partner closely with Design, GTM, and Customer teams to deliver measurable customer and commercial outcomes while operating at bothstrategic and hands-on execution depth.

This role includes building and leading ahigh-performing, globally distributed organization of Product Managers and Engineering leaders, and establishing consistent product and engineering operating standards across regions.

What You Will Own

Platform Strategy & Vision

• Define and drive theData & AI platform strategy, aligned to company and product vision
• Translate business goals intoroadmaps tied to measurable outcomes (adoption, revenue, retention)
• Establish aunified data and AI platform, leading the delivery of models, workflows, and capabilities across analytics, APIs, integrations, and AI services
• Rationalize fragmented capabilities into ascalable, reusable platform model
• Partner to drivetechnology unification and synergy strategies across regions, time zones, and global workforce environments

Data & AI Platform Leadership

• Build and evolve core platform capabilities including:
  • Data ingestion, pipelines (ETL/ELT), and real-time streaming
  • APIs, integration frameworks, and partner extensibility
  • Data models, governance, and metadata/lineage
  • Analytics, reporting, and reusable data products
• Define and executeAPI and ecosystem strategy, including partner monetization and platform access models
• Define and operationalizestandardized data packages and distribution modelsto support global consumption and regional needs

AI-Driven Product Transformation

• Identify and deliverAI use cases embedded into core workflows(not bolt-ons)
• LeverageLLMs, RAG architectures, and agentic AI patternsto improve customer outcomes and internal efficiency
• Define and scaleAI platform capabilities, including model lifecycle, RAG systems, agent orchestration, data pipelines, and governance
• Drive Engineering execution ofAI platform services and AI-assisted development practices

Execution & Delivery

• Drivehigh-quality, predictable executionacross multiple teams, regions, and time zones
• Define and evolve theproduct and engineering operating model, including team topology, platform vs. product boundaries, and delivery ownership
• Implement outcome-driven product and engineering practices across data, AI, and platform workstreams
• Ensure consistent delivery standards, tooling, and metrics across teams
• Own and standardize the global inventory, packaging, and delivery of data products, ensuring consistent, scalable, and reliable access across regions, time zones, and customer segments
• Remove blockers and drive accountability for results

Customer & Market Leadership

• Maintain deep understanding ofcustomer needs, industry trends, and competitive landscape
• Lead discovery and validation to ensure products solvehigh-value problems,clearly articulating value propositions tied to measurable clientoutcomes
• Represent the platforminternally andexternally through client engagement, thought leadership, andindustry presence

Commercial & GTM Alignment

• Partner with Sales, Marketing, and Customer Success ongo-to-market execution
• Support pricing, packaging, and monetization strategies for data and platform products
• Drive growth ofdata- and API-based revenue streams
• Own or materially influence revenue, adoption, and margin performanceof data and platform products

Stakeholder Leadership

• Partner effectively with senior executives across Product, Engineering, and GTM
• Communicate strategy, progress, and trade-offs clearly across stakeholders
• Represent the platform in executive forums and drive cross-functional alignment

Team Leadership

• Build, lead, and scale ahigh-performing, globally distributed organization of Product Managers and Engineering leadersacross North America, EMEA, and APAC
• Coach teams on strong product thinking, engineering excellence, platform mindset, and execution discipline
• Establish a consistent, high bar for product management and engineering practices

What Success Looks Like

• Aclear, adopted Data & AI platform strategyacross the organization
• Measurable improvement indata accessibility, platform adoption, and revenue impact
• AI capabilities embedded directly intocustomer workflows and products
• Reduced duplication and increased reuse viaplatform standardization
• Consistent, reliable global delivery of standardized data products across regions and time zones
• High-performing product and engineering organization operating withconsistent quality and velocity

Leadership, Product Management & Engineering

• 10+ years in Product Management and/or Engineering leadership, including management of Product Managers and technical teams
• Experience owningmulti-product SaaS or platform portfolios
• Proven ability to operate and influence at theexecutive level
• Strong experience withplatform product models and ecosystem thinking

Data, Analytics & AI

• Experience buildingdata and analytics platforms(data lakes, data warehouses, semantic models, pipelines, reporting)
• Strong understanding ofAPIs, integrations, and platform extensibility
• Practical experience applyingAI/ML, LLM-based capabilities, RAG systems, and agentic AIin products
• Understanding ofdata governance, semantic models, real-time data, and integration patterns

Execution & Delivery

• Track record of deliveringcomplex, scalable SaaS products
• Strong data-driven decision making and product metrics orientation
• Experience working acrossglobal, distributed teams

Commercial & Market Acumen

• Experience drivingproduct growth, adoption, and monetization
• Ability to develop business cases, pricing strategies, and ROI models

Technical & Platform Fluency

• Strong understanding of modern architectures:
  • SaaS platforms, microservices, APIs
  • Cloud platforms such asAzure (preferred), AWS, or GCP, including data platforms, compute, and distributed systems
  • Data pipelines, data warehouses, and CI/CD
• Experience withMicrosoft Fabric, Snowflake, or Databricksis a strong plus
• Comfortable engaging inproduct architecture and technical trade-offs

Communication & Influence

• Clear, direct communicator with strong executive presence
• Ability to influence across competing priorities and stakeholders
• Strong collaboration and cross-functional leadership skills

Education

• Bachelors degree required; Masters degree preferred in Computer Science, Engineering, Data Science, or a related field

Profile

• Systems thinker who seesplatforms, not point solutions
• Bias towardaction, outcomes, and measurable impact
• Comfortable withambiguity, scale, and transformation
• Ability tosimplify complex problems into actionable strategy
• Raises the bar, delivers results, and develops strong teams