Leader Data & AI Product Designer & Architect - F/H

📍 Job Overview

Job Title: Leader Data & AI Product Designer & Architect - F/H

Company: Wepoint

Location: Paris, France

Job Type: Full-Time

Category: Revenue Operations / Sales Operations / GTM Strategy (Data & AI Transformation)

Date Posted: May 26, 2026

Experience Level: 10+ Years

Remote Status: Hybrid

🚀 Role Summary

• Spearhead the design and architecture of data and AI products, focusing on scalability, governance, and business value delivery within transformation programs.

• Drive the productization of data and AI initiatives, translating complex business needs into concrete, deployable solutions that enhance operational efficiency and business performance.

• Lead and mentor multidisciplinary teams in the implementation of modern data platforms and agentic AI solutions, fostering a culture of innovation and continuous improvement.

• Act as a key liaison between business stakeholders, product teams, and technical architects to ensure seamless integration and alignment of data and AI strategies with organizational objectives.

• Contribute to the development and refinement of Wepoint's value proposition in Data Product and AI transformation, identifying and converting business opportunities.

📝 Enhancement Note: This role, while not strictly a traditional Sales or Revenue Operations role, is deeply embedded in the operational transformation of clients through Data and AI. The focus on "operating models," "processes," and "steering methods" directly impacts how businesses function, generate revenue, and manage their sales cycles. The role requires a strong understanding of business processes and how to leverage data and AI to optimize them, making it highly relevant to operations professionals. The "productization of data" and "API as a Product" aspects are crucial for enabling sales and revenue teams with accessible, governed data insights.

📈 Primary Responsibilities

• Design and architect scalable Data and AI products, meticulously defining metadata, SLAs, ownership, quality standards, and traceability.

• Lead the "Data as a Product" and "API as a Product" initiatives, championing the product vision and methodology to ensure user-centricity and business alignment.

• Develop and oversee modern data platforms designed as integral products to serve diverse user needs across the organization.

• Model complex business concepts (e.g., customer, master data) with a keen understanding of sector-specific nuances (retail, finance, industry), integrating these into robust data and AI architectures.

• Analyze and understand client business processes to inform and transform modeling and architectural choices, ensuring data and AI solutions directly support and optimize operational workflows.

• Design data and AI architectures that actively enable and transform operational processes, ensuring they are scalable, maintainable, and aligned with business objectives.

• Propose innovative designs for agentic AI products and a semantic layer optimized for business use cases, driving actionable insights and automated decision-making.

• Lead data and AI transformation programs, integrating platform modernization and AI use-case development into cohesive strategies.

• Adapt data strategies and architectures to various client organizational models, including centralized, decentralized, and federated approaches like data mesh.

• Contribute to structuring industrialized approaches for Data and AI Factories, ensuring efficient development and deployment pipelines.

• Reconcile diverse perspectives from architecture, modeling, governance, and product management to achieve a unified vision.

• Ensure alignment between business, product, and technical teams, fostering effective communication and collaboration.

• Lead multidisciplinary teams in complex environments, driving project success and team development.

• Implement scaled agile practices, including PI Planning and product backlog management, to optimize project delivery.

• Mentor team members and disseminate best practices in data and AI product design and architecture.

• Operate effectively within complex client environments, tailoring approaches to specific business and organizational contexts.

• Contribute to the development and refinement of Wepoint's Data Product value proposition.

• Identify and cultivate new business opportunities within client engagements.

• Support the creation of commercial proposals and offers.

📝 Enhancement Note: The responsibilities are heavily weighted towards strategic design, architecture, and leadership in Data and AI transformation. This implies a strong need for individuals who can translate business challenges into technical solutions and manage complex projects. The emphasis on "productization of data" and "agentic AI" points to a forward-looking role requiring expertise in modern data strategies and AI implementation.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Technology, or a related field is typically expected for this level of role. Advanced degrees or certifications in Data Architecture, AI, or Product Management would be highly advantageous.

Experience: Minimum of 10-15 years of significant experience in data-related fields, including data architecture, data modeling, and data platform management. Proven track record of leading complex data and AI transformation initiatives.

Required Skills:

• Advanced expertise in Data Modeling, applicable across diverse business sectors (e.g., retail, finance, industry).

• Deep understanding of business processes and their transformation through data and AI.

• Proficiency in designing and structuring Data Products (metadata, SLA, ownership, quality, traceability).

• Strong grasp of 'Data as a Product' and 'API as a Product' methodologies.

• Experience in building modern data platforms with a product-centric approach.

• Expertise in designing comprehensive data and AI architectures that support and transform operational processes.

• Ability to conceptualize and design agentic AI products and a business-use-case-oriented semantic layer.

• Proven ability to link business requirements, product vision, and technical execution.

• Experience in structuring and accelerating data transformations.

• Demonstrated leadership in managing multidisciplinary teams within complex environments.

• Strong transverse leadership and influencing skills.

• Excellent client-facing communication and stakeholder management capabilities.

• Pragmatic, value-oriented, and curious mindset.

• Experience with various organizational models for data (centralized, federated, data mesh).

Preferred Skills:

• Experience with Generative AI and Agentic AI use cases.

• Knowledge of Agile at Scale methodologies (e.g., PI Planning, product backlog management).

• Experience in business development and contributing to commercial proposals.

• Understanding of specific industry challenges and how to tailor data solutions.

• Familiarity with data governance frameworks and implementation.

📝 Enhancement Note: The experience requirement is substantial, indicating a senior leadership role. The emphasis on understanding business processes and translating them into technical solutions is critical for operations-focused roles. The "Leader" title suggests significant team management and strategic guidance responsibilities.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrations of designed Data Products, showcasing metadata, SLA definitions, ownership structures, and quality metrics.

• Case studies detailing the productization of data or APIs, highlighting the methodology, user adoption, and business impact.

• Architectural blueprints of modern data platforms designed as products, illustrating scalability, integration capabilities, and user accessibility.

• Examples of complex data models created for specific industry verticals, with clear explanations of how they support business processes.

• Documentation of AI product designs, particularly agentic AI solutions, outlining their intended functionality, integration, and value proposition.

• Evidence of leading data transformation programs, including project scope, methodologies used, challenges overcome, and quantifiable results.

• Examples of adapting data strategies to different organizational models (e.g., Data Mesh implementation).

Process Documentation:

• Workflow designs for data product lifecycle management, from ideation and design to deployment and iteration.

• Methodologies for industrializing data and AI solution development and deployment.

• Frameworks for measuring and reporting on the performance and impact of data products and AI solutions.

• Strategies for implementing and managing data governance across productized data assets.

• Processes for integrating business requirements into technical architecture and product roadmaps.

📝 Enhancement Note: For a role of this seniority, a robust portfolio is essential. It should not just list projects but demonstrate a strategic thought process, problem-solving capabilities, and measurable impact on business operations and value creation. The focus on "productization" and "industrialization" means portfolio pieces should highlight efficiency, scalability, and a product-management mindset.

💵 Compensation & Benefits

Salary Range: For a Leader Data & AI Product Designer & Architect with 10-15 years of experience in Paris, France, the estimated annual gross salary range is €90,000 - €130,000. This range can vary based on specific experience, negotiation, and the exact scope of responsibilities within the role.

Benefits:

• Tailor-made career paths with complementary options for business management and expertise development.

• Access to the Onepoint School, offering over 200 training courses for continuous professional development.

• Flexible working charter promoting work-life balance.

• Free access to an on-site medical clinic.

• Opportunities to participate in leisure and sports activities (music, photography, e-sport, yoga).

• Engagement in diversity and inclusion initiatives and working groups.

• Participation in significant company events like the Revolution Summit.

• Contributions to a company aiming for €1 billion in revenue within 4 years, indicating potential for growth and impact.

Working Hours: While the standard is likely 40 hours per week, the "flexible working charter" suggests a degree of autonomy and adaptability in managing work hours, common for senior roles focused on outcomes rather than strict time tracking.

📝 Enhancement Note: Salary estimates for senior roles in Paris are based on industry benchmarks for specialized technical and leadership positions. The benefits package emphasizes professional growth, well-being, and flexibility, which are attractive to experienced professionals.

🎯 Team & Company Context

🏢 Company Culture

Industry: Consulting and Technology Services. Onepoint operates at the intersection of business strategy and technological innovation, focusing on digital transformation for large enterprises and public sector organizations.

Company Size: Over 3,500 employees globally. This indicates a substantial organization with established processes, resources, and a broad client base, offering opportunities for significant impact and career progression.

Founded: 2002. With over 20 years of history, Onepoint has a proven track record and has experienced significant growth, demonstrating stability and a capacity for adaptation.

Team Structure:

• The role is within the Hub Smart Business Transformation (SBT) collective, which is dedicated to Data and AI-driven transformations. This suggests a specialized, high-impact team focused on cutting-edge technologies and strategic client initiatives.

• The team is likely composed of diverse experts in Data Science, AI, Architecture, Business Analysis, and Transformation Consulting.

• Reporting is expected to be to a senior leader or Partner within the SBT hub, with direct leadership of project-specific multidisciplinary teams.

Methodology:

• Data-Driven Transformation: Emphasis on leveraging Data and AI as tangible levers for sustainable performance.

• Product-Centric Approach: Designing platforms and data assets as governed, scalable, and business-oriented products.

• Agile at Scale: Implementation of agile methodologies for managing complex transformation programs.

• RESET Approach: Onepoint's commitment to economic, social, environmental, and technological responsibility, integrated into their operations and client engagements.

• Continuous Learning: Strong investment in employee upskilling, particularly in areas like Generative and Agentic AI.

Company Website: https://www.wepoint.com/

📝 Enhancement Note: Onepoint positions itself as a forward-thinking consultancy with a strong emphasis on innovation, employee development, and corporate responsibility. The Hub SBT is a strategic focus area, indicating significant investment and opportunity within this domain.

📈 Career & Growth Analysis

Operations Career Level: This role represents a senior leadership and expert position within the Data & AI transformation domain, akin to an Principal Architect or Director level. It demands a blend of deep technical expertise, strategic vision, and strong leadership capabilities to guide complex client engagements and internal initiatives.

Reporting Structure: The role reports to a senior executive within the Smart Business Transformation (SBT) Hub, likely a Partner or Director. The individual will be responsible for leading project teams, which may include consultants, architects, data scientists, and product managers, all working towards client transformation goals.

Operations Impact: The role has a direct and profound impact on client operations by fundamentally reshaping how they leverage data and AI. This includes optimizing operating models, transforming business processes, enhancing decision-making capabilities, and driving tangible business performance improvements. By productizing data and implementing agentic AI, this role empowers clients to achieve greater efficiency, agility, and competitive advantage.

Growth Opportunities:

• Strategic Leadership: Opportunity to shape Onepoint's Data Product and Agentic AI offerings, influencing the company's strategic direction in these critical areas.

• Technical Specialization & Expansion: Deepen expertise in emerging AI technologies (Generative AI, Agentic AI) and advanced data architecture patterns (e.g., Data Mesh expansion).

• Client Impact & Business Development: Lead high-profile transformation programs, build strong client relationships, and contribute significantly to identifying and converting new business opportunities.

• Mentorship & Community Building: Play a key role in mentoring junior consultants and contributing to the active knowledge-sharing community within Onepoint, including events like the Revolution Summit.

• Leadership Track: Potential to advance into senior leadership roles within the SBT Hub or broader consulting practice, managing larger teams and portfolios.

📝 Enhancement Note: This role is positioned as a pivotal point for career growth, offering pathways into deep technical mastery, strategic leadership, and significant business impact within a rapidly evolving field.

🌐 Work Environment

Office Type: Onepoint operates a network of modern office spaces designed to foster collaboration and innovation. These are not just traditional offices but "lieux de vie" (places to live/work) situated in key urban centers, reflecting a commitment to proximity with talent and work-life integration.

Office Location(s): The role is based in Paris, France. Onepoint also has offices in other French cities (Aix-en-Provence, Bordeaux, Lyon, Nantes, Rennes, Strasbourg, Toulouse) and globally (Australia, Belgium, Canada, Malaysia, Morocco, Singapore), indicating a broad operational footprint.

Workspace Context:

• Collaborative Spaces: Offices are designed to encourage teamwork, knowledge sharing, and informal interactions, supporting the "collectif" culture.

• Technology Enabled: Access to modern tools and technology infrastructure necessary for complex data and AI projects.

• Hybrid Work Model: The "flexible working charter" and "REMOTE" status (though the location is Paris) suggest a hybrid model is standard, allowing for a blend of office-based collaboration and remote work. This flexibility is crucial for managing complex projects and maintaining work-life balance.

• Community Integration: Opportunities to engage with colleagues through various activities, fostering a strong sense of community.

Work Schedule: The standard working hours are likely around 40 hours per week, but the emphasis on a "flexible working charter" indicates that the focus is on delivering results and achieving project milestones, allowing for some autonomy in managing daily schedules.

📝 Enhancement Note: The work environment is designed to be dynamic and supportive, balancing the demands of high-impact consulting with employee well-being and flexibility. The "lieux de vie" concept suggests a more holistic approach to the workplace than typical corporate environments.

📄 Application & Portfolio Review Process

Interview Process:

• 1st Exchange (HR): Approximately 30 minutes via Teams or in person. Focus on understanding candidate motivations, career aspirations, and initial fit with Onepoint's culture and values. Be prepared to articulate your interest in Data/AI transformation and Wepoint's specific approach (RESET, SBT Hub).

• 2nd Exchange (Operational): Approximately 1 hour via Teams or in person. This will likely delve into specific technical and architectural experiences. Prepare to discuss your background in data modeling, architecture design, and Data Product conceptualization.

• 3rd Exchange (Operational): Approximately 1.5 hours via Teams or in person. This interview will likely be more in-depth, potentially involving case study elements or complex problem-solving scenarios related to data transformation and AI implementation. Focus on demonstrating your strategic thinking and ability to bridge business and technical domains.

• 4th Exchange (Partner): Approximately 1 hour via Teams or in person. This final stage focuses on projecting your role within Onepoint, assessing your leadership potential, business development acumen, and long-term strategic alignment with the company's vision.

Portfolio Review Tips:

• Structure for Impact: Organize your portfolio to clearly showcase your experience in Data Product Design, Architecture, and AI implementation. Use a consistent structure for each case study: Problem, Your Role/Approach, Solution/Design, and Quantifiable Results/Impact.

• Highlight Process & Methodology: Emphasize the processes you followed for designing data products, architecting platforms, and implementing AI solutions. Detail your understanding and application of methodologies like 'Data as a Product,' Agile at Scale, and specific modeling techniques.

• Showcase Business Acumen: For each project, clearly articulate the business challenges addressed and the tangible value delivered. Quantify achievements wherever possible (e.g., improved efficiency by X%, reduced data latency by Y%, enabled Z new business capabilities).

• Demonstrate Leadership: Include examples where you led teams, mentored colleagues, or influenced stakeholders. Highlight your ability to reconcile different perspectives and drive consensus.

• Tailor to the Role: Select portfolio pieces that best align with the responsibilities of a Leader Data & AI Product Designer & Architect, focusing on complexity, scale, and strategic impact.

Challenge Preparation:

• Scenario-Based Problems: Be prepared for hypothetical scenarios where you'll need to design a data strategy, architect a platform, or propose an AI solution for a given business problem. Practice articulating your thought process clearly and logically.

• Technical Deep Dives: Anticipate questions on specific technologies, modeling techniques, architectural patterns (e.g., Data Mesh), and AI concepts.

• Leadership & Stakeholder Management: Consider how you would handle team conflicts, manage challenging stakeholders, or drive adoption of new data products/AI solutions.

• Business Value Articulation: Practice explaining complex technical concepts and their business implications in a concise and compelling manner.

📝 Enhancement Note: The multi-stage interview process suggests a thorough evaluation of both technical and leadership capabilities. A well-curated portfolio that demonstrates strategic thinking, practical application, and measurable business impact will be crucial for success.

🛠 Tools & Technology Stack

Primary Tools: While not explicitly listed, the role implies familiarity with a broad range of data and AI technologies. Expect to work with:

• Data Platform Technologies: Cloud-native data platforms (AWS, Azure, GCP), Data Lakes, Data Warehouses, Data Lakehouses.

• Data Modeling Tools: ER/Studio, Erwin, Lucidchart, or similar for conceptual, logical, and physical data modeling.

• Architecture Design Tools: Tools for diagramming complex systems and data flows.

• AI/ML Platforms: Frameworks like TensorFlow, PyTorch; MLOps tools; platforms for building and deploying AI models.

• Agentic AI Frameworks: LangChain, OpenAI APIs, or similar for developing AI agents.

• API Management Tools: For designing and managing APIs as products.

• Data Governance & Cataloging Tools: Collibra, Alation, or similar for metadata management, lineage, and quality.

Analytics & Reporting:

• BI Tools: Tableau, Power BI, Looker for data visualization and reporting.

• Data Querying: SQL proficiency is a given; experience with distributed query engines (e.g., Spark SQL, Presto).

CRM & Automation:

• While not directly managing CRM/Sales Ops tools, understanding how data products and AI solutions integrate with and enhance CRM functionalities (e.g., lead scoring, customer insights) is vital.

• Familiarity with workflow automation tools and concepts.

• Integration Tools: Understanding of ETL/ELT processes and tools (e.g., Informatica, Talend, Fivetran, dbt).

📝 Enhancement Note: The role requires a broad understanding of the modern data stack and AI ecosystem. The emphasis is on architecting solutions, so familiarity with platform capabilities and integration patterns is key. Practical experience with specific tools will vary, but a strong conceptual understanding of their purpose and integration is essential.

👥 Team Culture & Values

Operations Values:

• Innovation & Technology: A strong drive to leverage cutting-edge Data and AI technologies to solve complex business problems and create tangible value.

• Excellence & Quality: Commitment to delivering high-quality, scalable, and robust data products and AI solutions, adhering to best practices in design, architecture, and governance.

• Collaboration & Teamwork: Fostering a collective environment where knowledge is shared, diverse perspectives are valued, and teams work together effectively to achieve common goals.

• Client Focus & Value Creation: Dedication to understanding client needs deeply and delivering solutions that drive measurable business impact and sustainable performance.

• Responsibility & Sustainability: Adherence to Onepoint's RESET approach, integrating economic, social, environmental, and technological responsibility into all aspects of work.

Collaboration Style:

• Cross-Functional Integration: Actively bridging gaps between business, product, and technical teams to ensure alignment and shared understanding.

• Mentorship & Knowledge Sharing: Proactively sharing expertise, mentoring junior colleagues, and contributing to a culture of continuous learning and development.

• Agile & Iterative: Embracing agile principles to facilitate iterative development, rapid feedback loops, and adaptability in project execution.

• Open Communication: Encouraging open dialogue, constructive feedback, and transparent communication across all levels and disciplines.

• Problem-Solving Orientation: Approaching challenges with a pragmatic, solution-oriented mindset, fostering an environment where experimentation and learning from failures are accepted.

📝 Enhancement Note: The culture emphasizes a blend of technical excellence, strategic thinking, and collaborative spirit, underpinned by a strong sense of corporate responsibility. For operations professionals, this means a focus on process improvement, data-driven decision-making, and achieving measurable business outcomes.

⚡ Challenges & Growth Opportunities

Challenges:

• Bridging the Gap: Effectively translating complex, often ambiguous, business requirements into concrete, scalable data and AI product designs and architectures, especially across diverse industries.

• Pace of Technological Change: Staying abreast of rapid advancements in AI (especially Generative and Agentic AI) and data technologies, and integrating them effectively into client solutions.

• Organizational Transformation: Guiding clients through significant organizational and process changes required to adopt new data-driven operating models and AI capabilities.

• Balancing Vision and Pragmatism: Maintaining a forward-looking vision for data and AI while delivering practical, industrializable solutions that meet immediate business needs.

• Stakeholder Alignment: Achieving consensus and buy-in from diverse stakeholders (executives, business units, IT) with potentially competing priorities.

Learning & Development Opportunities:

• Advanced AI Specialization: Deep dive into Generative AI, Agentic AI, and their practical applications in business transformation through Onepoint's extensive training programs.

• Data Architecture & Product Leadership: Enhance skills in designing complex, scalable data platforms and mastering product management principles for data assets.

• Industry Expertise: Gain deeper insights into specific client industries (retail, finance, manufacturing) by working on diverse transformation projects.

• Consulting & Business Development: Develop skills in client relationship management, strategic consulting, and identifying/converting business opportunities.

• Leadership Development: Opportunities to lead larger teams, manage P&L for engagements, and ascend to senior leadership positions within Onepoint.

📝 Enhancement Note: This role presents significant intellectual challenges and opportunities for continuous growth, particularly in the rapidly evolving fields of AI and data product management.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you designed a data product from concept to implementation. What were the key considerations for its architecture, governance, and user adoption?" (Focus on productization, scalability, and business value.)

• "How would you approach architecting a data platform for a client in the retail sector, considering their unique operational processes and data challenges?" (Demonstrate industry understanding and architectural design skills.)

• "Walk us through your experience with agentic AI. How have you approached designing or implementing solutions using these technologies to drive business outcomes?" (Highlight practical AI application and strategic vision.)

• "How do you ensure alignment between technical architecture, data governance, and the strategic objectives of business units when leading a transformation program?" (Emphasize cross-functional leadership and strategic thinking.)

Company & Culture Questions:

• "Why Onepoint and specifically the Smart Business Transformation (SBT) Hub?" (Research Onepoint's mission, values, and the SBT Hub's strategic focus.)

• "How do you see your role contributing to Onepoint's RESET approach and commitment to responsible technology?" (Align your values with the company's.)

Portfolio Presentation Strategy:

• Narrative is Key: Don't just present slides; tell a compelling story for each case study. Start with the business problem, elaborate on your strategic approach and design choices, detail the solution, and conclude with the impact and lessons learned.

• Focus on "Why" and "How": Explain not just what you did, but why you made certain architectural or design decisions and how they led to specific outcomes.

• Quantify Impact: Use metrics and data to demonstrate the tangible business value of your work. This is crucial for operations-focused roles.

• Showcase Leadership: Highlight instances where you led teams, influenced stakeholders, or navigated challenges to achieve project success.

• Be Prepared for Deep Dives: Anticipate detailed questions about your specific contributions, technical choices, and the reasoning behind them.

📝 Enhancement Note: Preparation should focus on demonstrating strategic thinking, deep technical expertise in data and AI architecture, strong leadership, and a clear understanding of how to drive business transformation through technology.

📌 Application Steps

To apply for this operations-aligned Data & AI leadership position:

• Submit your application through the provided Workday link: https://onepoint.wd3.myworkdayjobs.com/WepointCA/job/Paris-France/Leader-Data---AI-Product-Designer---Architect---F-H_JR103070-2

• Curate Your Portfolio: Select and refine 2-3 key projects that best exemplify your experience in Data Product Design, Data Architecture, and AI implementation, focusing on complexity, scale, and business impact. Ensure clear articulation of your role, methodology, and quantifiable results.

• Tailor Your Resume: Optimize your resume to highlight keywords relevant to Data Architecture, Data Modeling, Data Product Management, Agentic AI, and Transformation Leadership. Quantify achievements and responsibilities to showcase your impact.

• Prepare Your Narrative: Practice articulating your career journey, motivations for joining Onepoint, and how your skills align with the role's requirements. Prepare to discuss your portfolio projects in detail, emphasizing strategic decision-making and problem-solving.

• Research Onepoint & SBT: Thoroughly understand Onepoint's business, culture (RESET approach), and the strategic importance of the Smart Business Transformation (SBT) Hub. Be prepared to discuss how your vision aligns with theirs.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.