Wayfinders Senior Managing Consultant - Data & AI

Fujitsu at a Glance 

Fujitsu is a leading information and communication technology company, headquartered in Japan, offering a full range of technology products, solutions, and services. Approximately 132,000 Fujitsu people support customers in more than 100 countries. We use our experience and the power of technology to shape the future of society with our customers. 

Our corporate culture places great value on bringing new, unimagined possibilities to fruition.  This mission has been the foundation of Fujitsu’s success since its inception 90 years ago. In an increasingly competitive world with an accelerating pace of change, Fujitsu must strive for continuous innovation. Each and every employee will rise to the challenge of creating new value amid changes in management, technology, society, and the marketplace. With a spirit of challenge, we are committed to the continuous creation of new value. Fujitsu wants innovators like you. 

Wayfinders is Fujitsu’s new business and technology management consulting firm built for the AI era. Our mission is to help clients define how they should harness the power of technology to outperform their peers and drive new frontiers of growth and profitability. We help clients from opportunity to outcome, by developing strategy, implementing it at scale, and capturing ROI.  Our approach weaves AI into the consulting process and focuses on building client capabilities to leverage AI at scale across the enterprise. 

Position Overview: Wayfinders Senior Managing Consultant – Data & AI

We are seeking a dynamic and experienced Senior Managing Consultant to join our Data & AI practice. This role is ideal for a strategic thinker with expertise in enterprise-wide AI and data transformation programs. Experience aligning AI strategy initiatives with business goals and driving measurable outcomes. The ideal candidate will have a proven ability to translate complex data and AI challenges into business value, crafting compelling strategies and presenting C-suite-ready roadmaps, and driving adoption of data-driven decisions. 

Key Responsibilities

Leadership

• Proven mentor, with demonstrated track record growing junior colleagues into successful consultants
• Drive client satisfaction and long-term relationship development.
• Clear experience with a project-dedicated model, leading day-to-day project management and integrating workstreams for complex projects with teams of 3+ junior personnel

Practice Development

• Experience supporting the proposal process & building relationships with mid-senior clients
• Contributes to project-level strategy, ensuring alignment with client objectives and firm methodologies
• Supports practice strategy and development of consulting offers to address market trends

Required Skills & Experience

Consulting & Industry Experience and Education

• 5+ years, typically in consulting or equivalent industry leadership (e.g. Head of Data for a midsized company)
• Excels in storytelling and stakeholder facilitation, bridging technical (e.g., data engineers) and business audiences with persuasive narratives, building trust, and navigating client dynamics with finesse. 
• Experience with US subsidiaries of Japanese multi-national firms is a plus.
• Advanced degree (PhD, MBA, MS in Data Science, or equivalent) from a top-tier institution preferred, though relevant experience can substitute

Leadership & Influence

• Ability to influence and engage senior stakeholders.
• Strong people leadership skills, including team building, coaching, and performance management.
• Proven track record leading interdisciplinary projects spanning clients & colleagues with diverse technical backgrounds (e.g. data engineering, data science, MLE, software engineering) and traditional business backgrounds (e.g. project managers, integrative management 

Technical & Industry Knowledge

• Skilled in designing scalable, cloud-native data architectures, integrating data lakes (e.g., Databricks Delta Lake), data warehouses (e.g., Snowflake, Google BigQuery), data meshes for decentralized ownership, and real-time streaming platforms (e.g., Apache Kafka, AWS Kinesis) to support dynamic use cases, e.g. logistics optimization, retail store transformation, &