Lead the design, governance, and adoption of AI-powered business solutions across the enterprise.
Responsibilities
Define and govern enterprise AI, automation, analytics, and agent-based architectures aligned with business transformation goals.
Design and deliver intelligent workflows that integrate AI agents, automation platforms, and enterprise data systems.
Evaluate and guide adoption of AI technologies including Copilot Studio, Copilot Agents, Claude, UiPath AI, Snowflake Cortex, and related platforms.
Establish reusable frameworks, governance standards, and guidelines for AI development, citizen developers, and the CBO Agent Marketplace.
Mentor global engineering teams and partner with IT, Security, Enterprise Architecture, and Data teams to deliver secure, scalable AI solutions.
Requirements
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent practical experience.
Nice to have: Master's degree or equivalent experience in Computer Science, Artificial Intelligence, Data Science, Information Systems, or a related field.
Nice to have: Hands-on experience with automation platforms such as UiPath or similar intelligent automation technologies.
Nice to have: Experience with AI platforms and technologies including Copilot Studio, AI agents, Snowflake Cortex, or similar enterprise AI solutions.
Nice to have: Familiarity with enterprise applications such as SAP, Teamcenter, RapidResponse, and Snowflake.
The role connects functional or market business priorities with the organization’s enterprise Data & AI strategy, governance, platforms and delivery model, acting as the entry point for all Data & AI demand.
Responsibilities
Own the function or market Data & AI backlog and its contribution to the three-year technology roadmap and annual strategic planning cycle.
Partner with stakeholders to define business problems, value, data needs and feasibility, classify requests into the appropriate delivery route, and jointly prioritize demand with DA&I.
Own end-to-end delivery of the Data & AI portfolio on time, within budget and to agreed scope, quality and business outcomes, coordinating business, IT, DA&I and external partners.
Ensure testing, release readiness, documentation and support models are in place.
Ensure solutions follow enterprise architecture, data management, security, integration and technology standards, securing required approvals before build starts.
Drive high-impact initiatives that deliver tangible business value through architectural strategy and hands-on execution, leading modern data platforms, generative AI, and intelligent automation.
Locations (2)
Bangalore, Karnataka, India
Chennai, Tamil Nadu, India
Responsibilities
Lead the end-to-end delivery of modern data platforms, generative AI, and intelligent automation
Shape enterprise data foundations, analytics architecture, AI/ML enablement, generative AI, knowledge retrieval, and intelligent automation capabilities
Influence end-to-end solution direction, enterprise standards, and reusable architecture patterns across the organization
Build long-term Data and AI capability through mentoring, coaching, reusable playbooks, and knowledge transfer
Own end-to-end architecture for Data and AI solutions aligned to enterprise strategy, business goals, and platform standards
Support the Group Data Office in managing and orchestrating data transformation initiatives across Richemont’s Maisons, Functions, Divisions and Regions.
Locations (3)
Bellevue, Switzerland
Meyrin, Geneva, Switzerland
Fribourg, Fribourg, Switzerland
Responsibilities
Assist in managing the portfolio of initiatives on the data transformation roadmap
Coordinate with cross-functional teams to create transformation roadmap, map interdependencies and track progress
Collaborate with Maisons and Group Functions to define program objectives and scope
Support communities of practice or forums to facilitate collaboration on data transformation initiatives
Build and organize resources, support materials and communication content
Lead enterprise-wide Data Transformation for ABB Robotics, defining strategy and building capabilities to establish data as a trusted enterprise foundation for business transformation, operational performance and digital and AI-enabled capabilities.
Responsibilities
Define and drive the enterprise Data Strategy
Establish the enterprise data operating model and governance
Develop enterprise data capabilities
Embed data into enterprise transformation
Shape data foundations for future technology and AI
Requirements
Bachelor's or Master's degree in Business, Engineering, Computer Science, Data Management or a related discipline
Lead enterprise-wide Data Transformation for ABB Robotics, defining the strategy and building the capabilities required to establish data as a trusted enterprise foundation for business transformation, operational performance and digital and AI-enabled capabilities.
Responsibilities
Define and drive the enterprise Data Strategy: Translate ABB Robotics’ business and transformation priorities into a focused Data Strategy, capability roadmap and measurable outcomes.
Establish the enterprise data operating model and governance: Build the enterprise data operating model, including data domains, ownership, stewardship, common principles and cross-domain decision mechanisms, in partnership with business owners, Global Process Owners and IS.
Develop enterprise data capabilities: Drive the coordinated development of data governance, Master Data Management, data quality, accessibility, reuse and the trusted data foundations required for Business Analytics and AI.
Embed data into enterprise transformation: Ensure data requirements and dependencies are addressed consistently across major business and platform transformations, reducing fragmentation and promoting reusable enterprise capabilities.
Shape data foundations for future technology and AI: Define strategic data capability requirements and work with IS and architecture teams to ensure the technology landscape supports the enterprise Data Strategy.
Requirements
Bachelor's or Master's degree in Business
Lead Analyst, Data Product
Johnson & Johnson Innovative Medicine · Posted Nov 4, 2026
Owns stakeholder relationships and the lifecycle of assigned MedTech Supply Chain data products, translating end-user needs into useful, governed data models and measurable business outcomes.
Responsibilities
Discover and prioritize business problems, decisions, workflows, use cases, and outcomes that data products must support through stakeholder workshops and interviews.
Translate prioritized use cases into a product charter with clear scope, success measures, acceptance criteria, requirements, domains, source systems, owners, consumers, and dependencies.
Own assigned data products across their lifecycle from discovery through deployment, marketplace publication, adoption, and enhancement, maintaining the roadmap, prioritized backlog, readiness evidence, metadata record, adoption plan, and performance scorecard.
Lead domain-aligned data product squad(s) and align business stakeholders, data stewards, data modelers, architects, engineers, platform teams, and delivery partners on priorities, responsibilities, decisions, and required artifacts and approvals.
Establish governance and build readiness by defining ownership, business definitions, metadata, data-quality requirements, semantic standards, and reusable data models validated against business use cases.
Requirements
Nice to have: Advanced Analytics
Nice to have: Analytical Reasoning
Nice to have: Coaching
Nice to have: Communication
Lead Analyst, Data Product
Johnson & Johnson Innovative Medicine · Posted Nov 4, 2026
Own stakeholder relationships and the lifecycle of assigned MedTech Supply Chain data products, translating end-user needs into useful, governed data models and measurable business outcomes.
Responsibilities
Discover and prioritize business problems, decisions, workflows, use cases, and outcomes that data products must support through stakeholder workshops and interviews.
Translate prioritized use cases into a product charter with clear scope, success measures, acceptance criteria, requirements, domains, source systems, owners, consumers, and dependencies.
Own assigned data products across their lifecycle from discovery through deployment, marketplace publication, adoption, and enhancement, maintaining the roadmap, prioritized backlog, readiness evidence, metadata record, adoption plan, and performance scorecard.
Lead domain-aligned data product squad(s) and align business stakeholders, data stewards, data modelers, architects, engineers, platform teams, and delivery partners on priorities, responsibilities, decisions, and required artifacts and approvals.
Establish governance and build readiness by defining ownership, business definitions, metadata, data-quality requirements, semantic standards, and reusable data models validated against business use cases.
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Head of Data TransformationABB · Zurich, Switzerland
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