Data Product Architect

Introduction

A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.

You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.

Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.

Your role and responsibilities

A Data Products Designer bridges the gap between data strategy, business outcomes, and user experience by designing data products that are valuable, usable, and scalable. They work closely with business stakeholders, data teams, and technology teams to ensure data products solve real problems, fit into existing business workflows, and deliver measurable impact.

Key Responsibilities:

Data Product Discovery & Framing:

Facilitate discovery workshops with business, data, and technology stakeholders.

Frame the problem statements, user needs, and business value of data products

Define clear hypotheses, success metrics, and KPIs.

User-Centered Data Product Design:

Understand and map user personas, journeys, and pain points.

Translate user and business needs into data product concepts, prototypes, and MVPs.

Ensure data products are designed with usability, transparency, and explainability in mind.

Data Product Specification:

Define the scope, features, and functionalities of data products.

Specify data sources, data quality requirements, and governance needs.

Collaborate with data architects and engineers to define data pipelines and services underpinning the product.

Agile Product Management:

Work with product owners and scrum teams to prioritize backlogs, refine user stories, and align sprints to business outcomes.

Manage stakeholder expectations and ensure alignment between business goals and data delivery.

Define and iterate on data product roadmaps.

Design Thinking & Service Design Application:

Apply design thinking and service design methods to the data product lifecycle.

Create service blueprints, data product canvases, and value proposition maps.

Facilitate ideation, prototyping, and user testing sessions.

Data Product Evangelism & Change Management:

Act as the voice of the user and advocate for data products as part of AI transformation.

Support organizational change by demonstrating the value of data products & AI to business teams

Support data literacy initiatives related to the designed products.

Required technical and professional expertise

Data Product Management:

Understanding of data product lifecycle, from ideation to decommissioning.

Ability to define data product strategies, value propositions, and roadmaps.

Familiarity with data product management tools (e.g., Data Product Canvas, Opportunity Solution Tree)

Design Thinking & Service Design:

Proficiency in applying design thinking to data products.

Skilled in service design, including mapping user journeys, service blueprints, and stakeholder ecosystems.

Strong facilitation skills for workshops and co-creation sessions.

Business & Domain Acumen:

Ability to translate complex business problems into data product opportunities.

Understanding of business models, KPIs, and success metrics.

Ability to work across multiple domains (e.g., financial services, retail, healthcare).

Data Literacy & Technical Awareness:

Solid understanding of data architecture, data platforms, APIs, and data services.

Ability to collaborate effectively with data engineers, data scientists, and architects.

Familiarity with data governance, data quality, and compliance considerations.

Consulting & Stakeholder Management:

Strong communication and storytelling skills to engage stakeholders at all levels.

Ability to manage cross-functional teams and navigate client environments.

Experience in change management, data literacy programs, and adoption strategies.

Preferred technical and professional experience

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IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.