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

📍 Job Overview

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

Company: OnePoint

Location: Paris, France

Job Type: FULL_TIME

Category: Data & AI Strategy / Architecture / Product Management

Date Posted: 2026-05-26T00:00:00

Experience Level: 10+ Years

Remote Status: Hybrid

🚀 Role Summary

• Lead the design and architecture of scalable data products and modern data platforms, integrating agentic AI solutions to drive significant business process transformation.

• Champion the concept of "Data as a Product" and "API as a Product," ensuring data is governed, scalable, and directly serves business needs.

• Drive the implementation of AI solutions, with a particular focus on agentic and generative AI, to unlock tangible and sustainable performance gains for clients.

• Foster a collaborative environment that bridges the gap between business objectives, product vision, and technical execution, ensuring alignment and value delivery.

📝 Enhancement Note: This role is positioned as a senior leadership position within the "Smart Business Transformation (SBT)" Hub, focusing on strategic data and AI initiatives. The emphasis on "productizing" data and AI, coupled with a strong architectural component, suggests a blend of strategic consulting, product ownership, and technical architecture expertise. The "F/H" designation indicates the role is open to all genders (Femme/Homme).

📈 Primary Responsibilities

• Design and structure robust data products, encompassing metadata, Service Level Agreements (SLAs), ownership, quality metrics, and lineage tracking.

• Drive the productization of data and APIs, acting as the guardian of the product vision and methodology to ensure user-centric adoption and value realization.

• Architect and build modern data platforms, conceptualized as true products that directly support and enhance user experiences and operational efficiency.

• Develop complex business concepts (e.g., client data, reference data) with deep consideration for sector-specific nuances (retail, finance, industry) and integrate these into robust data models and architectures.

• Design data and AI architectures that actively support and transform client operational processes, ensuring scalability and adaptability.

• Propose innovative solutions for agentic AI products and design semantic layers optimized for business use cases, enhancing decision-making and automation.

• Lead and participate in transformation programs that integrate data platforms, modernization efforts, and AI use cases, ensuring end-to-end value delivery.

• Adapt data strategies to diverse client organizational models, including centralized, decentralized, and federated approaches like Data Mesh.

• Contribute to the structuring and industrialization of Data/AI Factories, promoting efficiency and scalability in data operations.

• Reconcile and harmonize visions across architecture, modeling, governance, and product management to ensure strategic alignment.

• Facilitate seamless communication and collaboration between business, product, and technical teams to guarantee alignment with business objectives.

• Pilot multidisciplinary teams within complex project environments, leveraging agile at scale methodologies (e.g., PI Planning, product backlog management).

• Contribute to the skill development of teams through mentoring, knowledge sharing, and the diffusion of best practices in data and AI product design.

• Engage effectively in complex client environments, adapting approaches to specific business and organizational contexts.

• Actively participate in shaping and deploying OnePoint's "Data Product" value proposition with clients.

• Identify and convert new business opportunities, contributing to the development of commercial offers and proposals.

📝 Enhancement Note: The responsibilities highlight a blend of strategic advisory, hands-on architectural design, and product leadership. The emphasis on "industrialization" and "factory" concepts points to a need for process-oriented thinking and the ability to scale solutions. The role requires a deep understanding of both technical architecture and business processes, with a strong focus on delivering tangible business outcomes.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Business Administration, or a related field is typically expected for this level of seniority.

Experience: Minimum of 10-15 years of significant experience in data architecture, data modeling, and data platform implementation. Proven track record in guiding data and AI transformations within complex client environments.

Required Skills:

• Advanced expertise in data modeling, applied across diverse business sectors (e.g., retail, finance, industry).

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

• Proficiency in identifying industry-specific differences and adapting models accordingly.

• Mastery of data product concepts, including governance (SLAs, quality, lineage), and industrialization principles.

• Strong comprehension of organizational models (centralized, federated, decentralized) and their impact on data architectures, including Data Mesh.

• Ability to design comprehensive architectures integrating data, AI, governance, and business usage.

• Proven ability to connect business needs, product vision, and technical execution.

• Demonstrated capability to structure and accelerate data transformations.

• Strong leadership and transverse influence skills.

• Excellent client interaction and stakeholder management capabilities in complex environments.

• Pragmatic, value-oriented mindset with a high degree of curiosity.

• Expertise in Agile methodologies (e.g., PI Planning, backlog management).

Preferred Skills:

• Experience with agentic and generative AI implementation.

• Familiarity with Data/AI Factory concepts and industrialization best practices.

• Knowledge of data governance frameworks and tools.

• Experience in business development and contributing to commercial proposals.

• Fluency in French and English.

📝 Enhancement Note: The experience requirement of 10-15 years is substantial, indicating a need for seasoned professionals who can operate with a high degree of autonomy and strategic impact. The emphasis on understanding specific industry nuances and adapting models is a key differentiator for this role, moving beyond generic architectural solutions.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase case studies demonstrating the design and implementation of scalable data products, highlighting metadata, SLA, ownership, and quality frameworks.

• Present examples of "Data as a Product" or "API as a Product" initiatives, detailing the product vision, methodology, and business impact.

• Include architectural diagrams and conceptual models for modern data platforms that were designed and deployed, emphasizing user-centricity and operational efficiency.

• Detail projects involving the transformation of business processes through data and AI, clearly articulating the methodology, challenges, and quantifiable outcomes.

• Provide examples of complex data modeling scenarios, illustrating how sector-specific challenges were addressed and integrated into the architecture.

Process Documentation:

• Document the lifecycle of data product development, from ideation and design to governance and ongoing management.

• Illustrate the process of defining and implementing data governance policies, including SLAs, data quality standards, and lineage tracking.

• Outline methodologies used for building and scaling modern data platforms, including considerations for infrastructure, tooling, and user access.

• Detail the approach to integrating AI solutions, particularly agentic AI, into existing data architectures and business workflows, focusing on industrialization and scalability.

• Showcase experience in adapting data strategies to different organizational structures and implementing frameworks like Data Mesh.

📝 Enhancement Note: A strong portfolio is crucial. Candidates should be prepared to present detailed case studies that not only showcase technical expertise but also demonstrate strategic thinking, product management acumen, and a clear understanding of business value and process transformation. The ability to articulate the "why" behind architectural and product decisions will be key.

💵 Compensation & Benefits

Salary Range: Based on the seniority (10-15+ years of experience), the leadership aspect of the role, and the location in Paris, France, a competitive salary range for a Leader Data & AI Product Designer & Architect would likely fall between €80,000 and €120,000 gross annual salary. This estimate is based on industry benchmarks for senior data architects and AI consultants in major European tech hubs, adjusted for the French market and the specific demands of product design and architecture.

Benefits:

• Tailor-made career paths: Personalized development plans focusing on business management or expertise, with two complementary progression axes.

• Onepoint School: Access to an extensive training catalog (over 200 courses) for continuous learning and skill development throughout professional life.

• Flexible Working Charter: A policy that allows for flexible work arrangements, accommodating project needs and personal life.

• Medical Clinic Access: Free access to an on-site medical clinic for employee well-being.

• Leisure and Sports Activities: Opportunities to participate in various activities such as music, photography, e-sports, and yoga, fostering a healthy work-life balance.

• Diversity and Inclusion Programs: Active participation in initiatives focused on equality, plurality, and creating an inclusive work environment.

• Company Social Events: Regular team-building activities, convivial gatherings, and structured events like the Revolution Summit.

Working Hours: The role involves a standard 40-hour work week, typical for full-time positions in France, with flexibility offered through the company's charter.

📝 Enhancement Note: The salary range is an estimate. Actual compensation will depend on the candidate's specific experience, skills, and negotiation. The benefits package emphasizes continuous development, well-being, and work-life balance, aligning with modern employee expectations.

🎯 Team & Company Context

🏢 Company Culture

Industry: Consulting and Technology Services. OnePoint operates in a dynamic sector, advising businesses and public entities on technological and strategic transformations, with a strong focus on Data and AI.

Company Size: Over 3,500 employees. This indicates a large, established consulting firm with a broad range of services and a significant market presence. For operations professionals, this size offers opportunities for diverse project experiences, structured career paths, and access to a large internal network, but also requires navigating larger organizational structures.

Founded: 2002. With over 20 years of history, OnePoint has a solid foundation and has demonstrated significant growth, achieving over €500 million in revenue and aiming for €1 billion in the next four years. This growth trajectory suggests a company that is innovative, adaptable, and has a clear strategic vision.

Team Structure:

• The role sits within the Hub Smart Business Transformation (SBT), a dedicated collective focused on Data and AI-driven strategic transformations.

• The SBT Hub comprises experts who advise C-suites (General Management, Business, IT) on transforming operating models, processes, and steering methods using AI.

• The team emphasizes designing and deploying concrete, industrializable solutions that transform client practices and usage.

• There is a strong investment in upskilling consultants, particularly in generative and agentic AI.

Methodology:

• Data-Driven Transformations: Utilizing Data and AI as core levers for performance and transformation.

• Product-Centric Approach: Conceptualizing data and AI solutions as "products" with defined SLAs, ownership, and quality standards.

• Industrialization & Scalability: Focus on creating deployable, scalable, and concrete solutions rather than just recommendations.

• Agile & Collaborative: Employing agile methodologies and fostering cross-functional collaboration to deliver value.

• Continuous Learning: Significant investment in consultant upskilling, especially in emerging AI technologies.

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

📝 Enhancement Note: OnePoint's culture appears to be a blend of high-performance consulting with a strong emphasis on innovation, employee development, and corporate responsibility (RESET approach, RSE). The SBT Hub specifically focuses on cutting-edge Data and AI applications, positioning it as a forward-thinking and technically advanced part of the organization.

📈 Career & Growth Analysis

Operations Career Level: This is a senior leadership role, a "Leader" position, requiring at least 10-15 years of experience. It's positioned at the architect and principal consultant level, responsible for both strategic design and driving implementation. The role is pivotal in shaping the firm's Data and AI product strategy and its client offerings.

Reporting Structure: While not explicitly detailed, this role likely reports to a Partner or Director within the Smart Business Transformation (SBT) Hub. The "Leader" title implies direct leadership of project teams and potentially mentoring junior consultants. The role requires transverse coordination across business, product, and technical teams within client organizations and OnePoint.

Operations Impact: The role has a direct impact on client business outcomes by designing and implementing data and AI solutions that transform operating models, processes, and decision-making. It also contributes to OnePoint's strategic growth by identifying business opportunities, shaping the firm's value proposition, and potentially leading commercial efforts. The focus on "sustainable performance" and "real transformation" underscores the significant business impact expected.

Growth Opportunities:

• Expertise Deepening: Opportunities to become a recognized expert in Data Product Design, AI Architecture, and Agentic AI, potentially leading to a Partner-level role specializing in these areas.

• Leadership Development: Leading large-scale transformation programs and multidisciplinary teams, honing project management and client advisory skills.

• Business Development: Moving into roles with increased responsibility for client relationship management, opportunity identification, and commercial proposal development.

• Community Leadership: Contributing to the growth and innovation within the SBT Hub and the broader OnePoint community, potentially through speaking at events like Revolution Summit or developing new methodologies.

• Specialization: Focusing on specific industries or emerging AI technologies (e.g., Generative AI, Agentic AI) to build a niche expertise.

📝 Enhancement Note: The career path for this role appears to lead towards senior leadership within the consulting domain, potentially reaching Partner level, or specializing as a Chief Data/AI Architect within client organizations. The emphasis on both client-facing impact and internal contribution to OnePoint's offerings provides a robust growth trajectory.

🌐 Work Environment

Office Type: Hybrid work model. The job description mentions a "flexible working charter" and the possibility of Teams or in-person meetings for interviews, suggesting a blend of remote and office-based work. OnePoint has offices in major French cities.

Office Location(s): Paris, France. OnePoint also has locations in Aix-en-Provence, Bordeaux, Lyon, Nantes, Rennes, Strasbourg, and Toulouse in France, as well as international offices. The primary location for this role is Paris.

Workspace Context:

• Collaborative Environment: The role requires close collaboration with various internal teams (SBT Hub, other practice areas) and external client teams (business, IT, product). The emphasis on "community active" within the Hub suggests a supportive internal network.

• Operations Tools and Technology: While specific tools are not detailed, the role inherently involves working with modern data platforms, AI/ML tools, data modeling software, and collaboration platforms. Access to these technologies is implicit.

• Team Interaction: Significant interaction with clients to understand their needs and present solutions, as well as close collaboration with OnePoint colleagues for knowledge sharing, mentoring, and proposal development.

Work Schedule: Standard 40-hour work week, with flexibility expected due to the nature of consulting projects and client demands. The "flexible working charter" indicates an effort to balance project requirements with employee well-being.

📝 Enhancement Note: The hybrid model and flexible charter suggest a modern work environment that values autonomy and work-life balance, while still promoting in-person collaboration essential for consulting. The Paris location places the role in a major European business hub.

📄 Application & Portfolio Review Process

Interview Process:

• 1st Exchange (RH): 30 minutes, typically via Teams or in-person. Focus on candidate's motivations, career aspirations, and a general introduction to OnePoint.

• 2nd Exchange (Operational): 1 hour, Teams or in-person. Deeper dive into the candidate's experience, particularly related to data architecture, product design, and AI. Expect questions about specific projects and technical approaches.

• 3rd Exchange (Operational): 1.5 hours, Teams or in-person. Likely a more in-depth technical and strategic discussion, potentially involving case study elements or problem-solving scenarios related to data products and AI architecture.

• 4th Exchange (Partner): 1 hour, Teams or in-person. Focus on strategic fit, leadership potential, business development capabilities, and the candidate's vision for the role and their contribution to OnePoint.

Portfolio Review Tips:

• Structure: Organize your portfolio by key themes: Data Product Design, Data Architecture, AI Implementation, Business Process Transformation, and Leadership.

• Case Study Depth: For each project, clearly articulate the business challenge, your specific role and responsibilities, the solutions designed and implemented (including architecture, models, and product features), the technologies used, the challenges faced, and most importantly, the quantifiable business impact and ROI.

• Data Product Focus: Explicitly highlight how you approached "Data as a Product," including governance, SLAs, quality, and user adoption strategies.

• AI Integration: Showcase how you integrated AI (especially agentic/generative AI) into business processes, detailing the problem solved and the value created.

• Visuals: Use clear diagrams, flowcharts, and architecture blueprints to illustrate complex concepts.

• Conciseness: Be prepared to present your portfolio concisely, focusing on key achievements and demonstrating your strategic thinking and problem-solving abilities.

Challenge Preparation:

• Scenario-Based Questions: Expect to be presented with hypothetical client scenarios related to data strategy, AI implementation, or data product development. Be prepared to outline your approach, potential challenges, and recommended solutions.

• Architectural Design: You might be asked to sketch out an architecture for a specific use case or critique an existing one.

• Product Strategy: Prepare to discuss how you would define a data product roadmap, prioritize features, and manage stakeholder expectations.

• Agile & Transformation: Be ready to discuss how you would lead transformation initiatives using agile principles and manage change within client organizations.

📝 Enhancement Note: The multi-stage interview process indicates a thorough evaluation. Candidates should prepare to articulate their experience not just technically, but also in terms of strategic impact, leadership, and business development. The portfolio review is a critical element, requiring evidence of successful, impactful projects.

🛠 Tools & Technology Stack

Primary Tools:

• Data Modeling & Architecture Tools: ER/Studio, Sparx Enterprise Architect, Lucidchart, draw.io, Visio, or similar tools for conceptual, logical, and physical data modeling, and architecture design.

• Data Platform Technologies: Experience with various cloud data platforms (e.g., AWS Redshift, S3, Glue; Azure Synapse Analytics, Data Lake Storage, Databricks; Google Cloud Platform BigQuery, Dataflow, Dataproc) is highly relevant.

• AI/ML Platforms & Libraries: Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and cloud-based AI services (e.g., AWS SageMaker, Azure ML, Google AI Platform). Specific expertise in agentic AI and generative AI tools (e.g., LangChain, OpenAI API, Hugging Face) is a strong plus.

• Data Governance & Catalog Tools: Solutions like Collibra, Alation, Azure Purview, or similar for metadata management, data lineage, and policy enforcement.

Analytics & Reporting:

• BI Tools: Experience with tools such as Tableau, Power BI, Qlik Sense for data visualization and reporting, especially in understanding how data products will be consumed.

• Data Warehousing & Lakehouse Concepts: Understanding of technologies and methodologies for storing and querying large datasets.

CRM & Automation:

• CRM Systems: Familiarity with major CRM platforms like Salesforce, Microsoft Dynamics, or HubSpot, to understand how data products integrate with sales and customer management processes.

• ETL/ELT Tools: Experience with tools like Talend, Informatica, Fivetran, or cloud-native services for data integration.

• Orchestration & Workflow Tools: Tools like Apache Airflow, Prefect, or cloud-specific workflow services for managing data pipelines and AI model deployment.

📝 Enhancement Note: While specific tools are not listed, the role demands a broad understanding of the modern data and AI ecosystem. Candidates should be prepared to discuss their experience with cloud-native data platforms, AI/ML frameworks, and data governance solutions. The emphasis on "product" implies familiarity with API management and potentially microservices architectures.

👥 Team Culture & Values

Operations Values:

• Innovation & Transformation: A core value is driving significant transformations for clients using cutting-edge Data and AI technologies. This requires a proactive, forward-thinking mindset.

• Excellence & Quality: Commitment to delivering high-quality, industrializable solutions that meet rigorous standards (SLAs, data quality).

• Collaboration & Community: Strong emphasis on teamwork, knowledge sharing, and mutual support within the SBT Hub and across OnePoint.

• Client Centricity & Value Creation: Focusing on understanding client needs and delivering tangible business value and sustainable performance improvements.

• Continuous Learning & Agility: Encouraging ongoing professional development and adapting to new technologies and methodologies.

Collaboration Style:

• Cross-functional Integration: Seamless collaboration between business strategists, product managers, architects, data scientists, engineers, and client stakeholders.

• Agile & Iterative: Working in agile sprints, with regular feedback loops and iterative development to ensure alignment and rapid response to evolving needs.

• Knowledge Sharing: Active participation in community events, internal workshops, and mentoring to disseminate expertise and best practices.

• Empowerment & Autonomy: While collaborative, the senior nature of the role also implies a high degree of autonomy and ownership over designs and strategies.

📝 Enhancement Note: OnePoint's values seem to foster an environment where innovation is encouraged, quality is paramount, and continuous improvement is a way of life. The collaborative and community-oriented aspects are crucial for a consulting firm, ensuring that expertise is shared and leveraged effectively across client engagements.

⚡ Challenges & Growth Opportunities

Challenges:

• Bridging Technical and Business Divides: Effectively translating complex technical concepts (Data Architecture, AI) into clear business value and actionable strategies for diverse client stakeholders.

• Navigating Complex Client Organizations: Adapting to varied client cultures, legacy systems, and organizational structures to implement new data and AI solutions.

• Keeping Pace with AI Advancements: The rapid evolution of AI, particularly generative and agentic AI, requires continuous learning and adaptation to integrate the latest innovations effectively.

• Industrializing Solutions: Moving beyond proof-of-concepts to build truly scalable, robust, and maintainable data products and AI systems in client environments.

• Data Governance Implementation: Successfully embedding robust data governance practices (quality, lineage, ownership) within client organizations, which can often be a cultural hurdle.

Learning & Development Opportunities:

• Specialized AI Training: Deep dives into generative AI, agentic AI, and related fields through OnePoint's extensive training programs.

• Industry Best Practices: Exposure to diverse client industries provides opportunities to learn unique sector-specific challenges and solutions.

• Architectural Leadership: Developing expertise in designing complex, scalable, and resilient data architectures for large enterprises.

• Product Management Skills: Enhancing skills in defining product vision, roadmaps, and managing product lifecycles for data and AI offerings.

• Mentorship: Opportunities to mentor junior consultants and lead teams, developing leadership and people management capabilities.

• Industry Events: Participation in conferences and summits (like Revolution Summit) to stay abreast of industry trends and network with peers.

📝 Enhancement Note: The challenges presented are typical for senior roles in transformative technology consulting, requiring strong problem-solving, adaptability, and strategic thinking. The growth opportunities are well-aligned with advancing expertise in high-demand areas like AI and data architecture.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to design a data product from scratch. What was your methodology, what challenges did you face, and what was the business outcome?" (Focus on process, product thinking, and impact.)

• "How would you approach building an agentic AI solution for a client in the retail sector? What architectural considerations would be paramount?" (Assess understanding of AI application, architecture, and industry context.)

• "Imagine a client wants to implement a Data Mesh. What are the key architectural and organizational prerequisites, and how would you lead this transformation?" (Tests knowledge of distributed data architectures and change management.)

Company & Culture Questions:

• "What interests you most about OnePoint's RESET approach and its focus on sustainable transformation?" (Demonstrate research and alignment with company values.)

• "How do you see yourself contributing to the Smart Business Transformation (SBT) Hub's mission and community?" (Showcase understanding of team dynamics and desire for collaboration.)

Portfolio Presentation Strategy:

• Narrative Arc: Structure your portfolio presentations around compelling stories: problem, solution, execution, and impact.

• Quantify Everything: Whenever possible, use numbers to demonstrate the impact of your work (e.g., X% increase in efficiency, Y% reduction in costs, Z% improvement in data quality).

• Visual Aids: Use clear, professional slides with diagrams, architecture blueprints, and key metrics. Avoid text-heavy slides.

• Focus on "Why": Be prepared to explain the rationale behind your technical and product decisions, linking them back to business objectives.

• Tailor to the Role: Emphasize projects that showcase your expertise in data products, AI architecture, and business process transformation.

📝 Enhancement Note: Candidates should prepare specific examples that demonstrate their ability to think strategically, lead technically, manage product lifecycles, and drive tangible business outcomes. The interview process appears to be structured to assess these capabilities thoroughly.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided link on the OnePoint Workday portal.

• Portfolio Customization: Curate your resume and portfolio to highlight your most relevant experience in Data Product Design, Data Architecture, AI Implementation, and Business Transformation. Prepare 2-3 detailed case studies that exemplify your capabilities in these areas.

• Resume Optimization: Ensure your resume clearly lists your years of experience, specific technical skills (data platforms, AI frameworks, modeling tools), and achievements using keywords from the job description (e.g., Data Product, AI Architecture, Agentic AI, Data Governance, Scalability, Industrialization).

• Interview Preparation: Practice articulating your experience using the STAR method (Situation, Task, Action, Result) for behavioral questions. Prepare to discuss your approach to strategic challenges and present your portfolio confidently.

• Company Research: Thoroughly research OnePoint, its Smart Business Transformation (SBT) Hub, its RESET approach, and recent news or projects. Understand their value proposition and how your skills align with their mission.

⚠️ 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.