Director – Group Product Manager, Data & AI Studio Capability

Job Description

Director – Group Product Manager, Data & AI Studio Capability

Role Overview

The Director – Group Product Manager, Data & AI Studio Capability will lead the end-to-end product portfolio for the Data & AI Studio , a foundational capability that enables development, deployment, and operation of enterprise data and AI products. The Data & AI Studio serves as a core enablement layer powering multiple products and use cases , providing standardized capabilities across data ingestion, processing, transformation, and AI/ML development and orchestration. This role is accountable for product strategy, execution, adoption, and value realization of the Studio capability, ensuring it operates as a scalable, reusable, and platform-aligned product ecosystem . The role also carries full P&L accountability , including investment decisions, prioritization, and value delivery across the portfolio. The Director will lead a team of product managers and architects , working closely with engineering, enterprise platform teams, and enterprise architecture to deliver consistent, high-impact outcomes.

Key Responsibilities Product Ownership – Data & AI Studio Capability Own the end-to-end product strategy, roadmap, and lifecycle for the Data & AI Studio capability

Define how the Studio evolves as a multi-tenant, reusable enablement platform supporting diverse products and use cases

Ensure alignment between product vision, platform capabilities, and business priorities

P&L Ownership & Value Realization

Own P&L accountability for the Studio capability, including: Investment prioritization

Capacity planning

Value realization across product adoption and usage

Drive decisions that balance cost, scalability, and business impact

Ensure measurable outcomes across: Product adoption

Capability utilization

Business value delivered

Capability Definition & Evolution Define and evolve core Studio capabilities, including: Data ingestion frameworks

Pipeline orchestration and workflow management

Data processing and transformation layers

AI/ML development and operationalization

Ensure capabilities are: Modular and extensible

Reusable across multiple products

Aligned with enterprise platform and architecture standards

Execution & Delivery Leadership Drive end-to-end execution across Studio capabilities and product teams

Establish strong execution discipline, including: Sprint and release management

Roadmap tracking and milestone governance

Ensure alignment between product commitments, engineering delivery, and platform dependencies

Engineering & Platform Alignment Partner closely with engineering leadership to deliver robust and scalable capabilities

Ensure alignment with: Enterprise platform teams

Underlying cloud and data platform ecosystems

Drive adoption of shared services, standardized patterns, and reusable platform capabilities

Consumption & Adoption Model Define how the Studio capability is: Consumed by multiple product teams

Adopted across the organization

Establish clear patterns for: Onboarding

Capability reuse

Avoidance of redundant development efforts

Drive scale through consistent and repeatable consumption models

Team Leadership – Product Managers & Architects Lead and develop a team of product managers and architects responsible for Studio sub-capabilities

Define clear ownership across: Capability domains

Delivery outcomes

Build a high-performing organization focused on: Accountability

Execution discipline

Scalable product thinking

Stakeholder & Portfolio Alignment Engage with product leaders and stakeholders to: Align on capability needs and priorities

Ensure Studio roadmap reflects enterprise demand

Act as the single point of accountability for Studio product direction

Expected Outcomes A scalable, well-defined Data & AI Studio capability powering multiple products

Strong adoption of Studio capabilities across product teams

Reduced duplication and improved efficiency in data and AI development

Consistent and standardized approaches to: Data ingestion

Pipeline orchestration

AI/ML workflows

Measurable business impact through effective P&L management and value realization

Experience & Profile Required Qualifications 10+ years of experience in product management , including leadership across complex, platform-based products

Proven experience owning end-to-end product portfolios with P&L accountability

Strong understanding of: Data pipelines and processing

AI/ML development lifecycle

Platform-based product architectures

Demonstrated ability to lead multi-disciplinary teams (product + architecture)

Technology exposure Databricks

Matillion, DBT or similar

Collibra or similar

Dataiku, Sage maker or similar

Agentic AI awareness

Preferred Qualifications

• Experience building or managing enterprise data or AI platforms

• Experience driving platform adoption across multiple product teams

• Experience within global delivery models (US and India)

• Leadership Characteristics Strong operator with focus on execution, scale, and measurable outcomes

• Product leader who understands platforms as enabling ecosystems

• Ability to manage complexity across multiple products, capabilities, and stakeholders

• High accountability mindset with ownership of outcomes, value, and delivery

Required Skills: Business Intelligence (BI), Business Management, Database Administration, Data Engineering, Data Management, Data Modeling, Data Pipelines, Data Visualization, Delivering Value, Design Applications, Enterprise Architecture (EA), Enterprise Data, Enterprise Data Management, Enterprise Operations, Financial Decision Making, Information Management, Leadership, Prioritization, Product Management, Product Strategies, Software Development, Software Development Life Cycle (SDLC), System Designs Preferred Skills:

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Job Posting End Date: 07/18/2026 *A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.