Head of Data & AI

Position: Global Head of Data & AI Practice

Location: Dallas/ California / Atlanta

Engagement Type: Full Time

Client: Confidential

About Client:

This position is with the largest specialised player focused on the Connectedness industry — serving leading telcos, media companies, and technology platform providers across the globe. With a presence spanning Americas, EMEA, and Asia-Pacific, client combines deep domain expertise with cutting-edge Data & AI capabilities to drive hyper-growth and transformation for its clients. The Data & AI Practice sits at the heart of client''s growth strategy, delivering next-generation AI, data modernisation, cloud, and analytics solutions at scale.

Role Overview

This is a global leadership role for a practitioner-turned-strategist who combines deep architectural expertise with the commercial acumen to build and scale a world-class Data & AI practice. As Global Head of Data & AI Practice, you will own the front-end remit of the practice worldwide: P&L accountability, offering creation, go-to-market execution, customer advisory and consulting, thought leadership, and strategic partnerships. You will be a close and influential partner to delivery leadership, ensuring offerings are grounded in delivery reality and that clients receive a seamless experience from pursuit through to outcome. You will unify regional presales functions (Americas, Europe and India) under a coherent global strategy and serve as Prodapt''s most senior Data & AI voice with clients.

Reporting Structure & Scope

Direct Reports:

• Americas Presales Leader(s) (Data Modernisation & Platforms) — Canada based
• India-based Presales Team — supporting global pursuit and solutioning activity
• EMEA Presales Leader(s)

Functional Accountability (Owned):

• Global Data & AI Practice P&L — revenue, margin, and growth targets
• Offering portfolio, pricing strategy, and competitive differentiation
• GTM motions across all verticals and geographies
• Customer advisory and consulting — C-suite advisory engagements, strategic assessments, and solution origination
• Partner alliances and co-sell ecosystems (hyperscalers, ISVs, data platform vendors)

Key Working Relationships:

• Global and Regional Delivery Leaders — close partnership to shape delivery models, resolve escalations, and embed offerings into delivery practice
• Prodapt Sales Leadership — pipeline generation, deal qualification, and pursuit strategy
• CTO / Technology Office — alignment on innovation agenda and technical standards

Key Responsibilities

1. Global P&L Ownership & Business Growth

• Own and drive the global Data & AI Practice P&L — revenue, bookings, margin, and pipeline health.
• Define multi-year growth strategy and annual operating plans aligned to Prodapt''s global ambitions.
• Set revenue targets across geographies (Americas, EMEA, APAC/India) and hold regional leads accountable.
• Identify and pursue large-deal opportunities ($10M–$100M+) in partnership with sales, presales, and delivery leadership.
• Build the business case and investment rationale for new capability areas, white-space markets, and adjacent offerings.

2. Offering Creation & Portfolio Management

• Design, own, and continuously evolve the global Data & AI offering portfolio — covering data modernisation, cloud data platforms, AI/ML engineering, Generative AI, Agentic AI, LLMOps, and AI infrastructure.
• Build differentiated, industry-tuned solutions for Telco, Media, Life Sciences, Banking, and other key verticals.
• Translate architectural innovation into commercially packaged offerings — with defined scope, commercial model, and reference customer stories.
• Define pricing frameworks, commercialisation strategies, and deal-shaping playbooks for the practice.
• Maintain a live competitive intelligence view and evolve offerings ahead of market shifts.
• Own the development of reusable accelerators, reference architectures, and solution frameworks that underpin presales quality and accelerate delivery ramp-up in collaboration with delivery teams.

3. Go-To-Market (GTM) Strategy & Execution

• Define and execute integrated GTM strategies across all geographies, verticals, and partner channels.
• Work closely with the Americas Presales Leader and India Presales Team to align solutioning, pursuit, and pipeline generation.
• Champion deal shaping and solution strategy for marquee and strategic pursuits globally — providing senior architectural and commercial oversight.
• Establish and govern the global presales operating model: qualification frameworks, win strategies, proposal quality, and conversion metrics.
• Drive demand generation through executive engagement, industry events, partner ecosystem activities, and digital channels.
• Ensure GTM execution is grounded in real buyer insight — engaging directly with CDO, CIO, CTO, and Chief AI Officer stakeholders.

4. Thought Leadership & Market Positioning

• Establish Prodapt as a recognised Data & AI authority — through published POVs, whitepapers, analyst engagements, conference keynotes, and media contributions.
• Lead and participate in C-suite advisory sessions, industry roundtables, and executive workshops globally.
• Build and maintain a personal profile as a credible, practitioner-level thought leader in enterprise AI, data modernisation, and agentic/generative AI.
• Translate emerging technologies (Lakehouse, Data Mesh, AI Agents, Sovereign AI, FinOps for Data) into actionable enterprise narratives.
• Represent Prodapt at flagship industry events (Gartner Data & Analytics, Databricks Summit, Snowflake Summit, AWS re:Invent, etc.).

5. Strategic Partnerships & Alliances

• Own and develop strategic alliances with hyperscalers (Microsoft Azure, AWS, Google Cloud Platform) and data platform leaders (Databricks, Snowflake, dbt Labs, Fivetran, etc.).
• Negotiate and manage partnership tiers, co-sell agreements, and joint GTM programmes with key technology vendors.
• Leverage partner ecosystems to expand market reach, co-develop solutions, and access joint funding (MDF, co-sell, POC credits).
• Build relationships with Gartner, Forrester, and other analyst firms to shape market perception and influence evaluation shortlists.
• Identify and evaluate acquisition targets, investment opportunities, or white-label partnerships that accelerate practice scale.

6. Customer Advisory & Consulting

• Own Prodapt''s Data & AI advisory and consulting function — acting as the most senior practitioner voice in client-facing strategic engagements.
• Lead executive-level advisory sessions with CDO, CIO, CTO, and Chief AI Officer stakeholders across key accounts and prospect organisations.
• Conduct structured Data & AI maturity assessments, strategic roadmaps, and transformation blueprints as named advisory engagements.
• Originate new opportunities through advisory-led consulting relationships — converting strategic conversations into qualified pursuits.
• Define and standardise Prodapt''s consulting methodology for Data & AI — frameworks, assessment tools, discovery workshops, and CXO presentation standards.
• Serve as executive sponsor on strategic client relationships, providing continuity and credibility from advisory through to delivery handoff.
• Build a small, senior advisory bench capable of conducting high-quality CXO engagements independently across regions.

7. Practice Development & Team Leadership

• Build and lead a globally distributed, high-performing Data & AI GTM team — covering presales, advisory, architecture, and offering management functions. Delivery teams are not in scope.
• Establish a culture of innovation, continuous learning, and technical excellence across all practice layers.
• Drive capability development across Generative AI, Agentic AI, cloud data platforms, data engineering, and AI ethics/compliance.
• Develop clear career pathways and talent management frameworks for Data & AI advisory and presales professionals globally.
• Work in close partnership with Delivery Leadership to ensure offerings are backed by scalable, repeatable delivery models and that client commitments are achievable.
• Mentor senior architects, presales leaders, advisory practitioners, and emerging practice talent.

8. AI & Data Innovation

• Stay ahead of the curve on enterprise AI innovation — Generative AI, Agentic AI, LLMOps, AI compute infrastructure, and Sovereign AI.
• Define Prodapt''s innovation agenda for Data & AI: incubate new solution ideas, sponsor internal R&D, and validate with early adopter clients.
• Develop frameworks for responsible AI, AI governance, ethics, and compliance (GDPR, EU AI Act, sector-specific regulation).
• Leverage hands-on architectural insight to stress-test offerings, review high-stakes solution designs, and provide technical credibility in client engagements.

Required Skills & Experience

1. Leadership & Commercial:

• 15+ years in Data & AI / Technology, with at least 5 years in a senior practice leadership or P&L ownership role.
• Proven track record of building and scaling Data & AI practices in a consulting, systems integration, or managed services environment.
• Experience managing a global team across multiple geographies with direct reports in at least two regions.
• Demonstrated success in winning large-scale transformation programmes ($10M–$100M+) and advising clients through complex data and AI transformation journeys.
• Strong commercial instincts: business development, deal shaping, pricing, margin management, and pipeline discipline.

2. Hands-On Technical Foundation (Essential):

• Prior hands-on career as a Data Architect, Enterprise Architect, or Solutions Architect is strongly preferred — practitioner credibility is a key differentiator for this role.
• Deep expertise in modern data platform architectures: Lakehouse, Data Mesh, Data Warehouse modernisation (Teradata/Oracle/Netezza to Snowflake/Databricks/BigQuery).
• Solid understanding of cloud data platforms: Microsoft Azure (Fabric, Synapse, ADLS), AWS (Redshift, Glue, Lake Formation), Google Cloud Platform (BigQuery, Dataproc, Dataplex).
• Strong working knowledge of AI/ML engineering, MLOps, LLMOps, Generative AI, and Agentic AI frameworks.
• Familiarity with data governance tooling: Unity Catalog, Alation, Collibra, Purview, Snowflake governance, or equivalent.
• Ability to review, challenge, and guide architectural decisions on complex programmes without being a bottleneck.

3. GTM & Offering:

• Proven experience creating commercial offerings, go-to-market programmes, and sales plays for data or AI services.
• Track record of building and operationalising presales functions — from qualification through to proposal and contract.
• Experience managing hyperscaler and ISV partnerships (preferred: Microsoft, Databricks, Snowflake, AWS).
• Demonstrated thought leadership: published content, public speaking, analyst interaction, or executive advisory.

Preferred Qualifications

• Advanced degree in Computer Science, Engineering, Data Science, or a related field.
• Certifications in Enterprise Architecture (TOGAF, ZACHMAN), Cloud (Azure Expert, AWS SA Pro, Google Cloud Platform Professional Data Engineer), or AI/ML platforms.
• Recognised industry thought leader with a public profile in enterprise AI and data transformation.
• Prior experience in Telco, Media, or Connectedness-adjacent industries is a strong differentiator.
• Familiarity with responsible AI frameworks, EU AI Act compliance, and sovereign AI considerations.
• Experience with agentic AI architectures, LLMOps platforms, and AI compute infrastructure (GPU-as-a-service, sovereign AI clusters).

Position: Global Head of Data & AI Practice

Location: London, UK

Engagement Type: Full Time

Client: Confidential

About Client:

This position is with the largest specialised player focused on the Connectedness industry — serving leading telcos, media companies, and technology platform providers across the globe. With a presence spanning Americas, EMEA, and Asia-Pacific, client combines deep domain expertise with cutting-edge Data & AI capabilities to drive hyper-growth and transformation for its clients. The Data & AI Practice sits at the heart of client''s growth strategy, delivering next-generation AI, data modernisation, cloud, and analytics solutions at scale.

Role Overview

This is a global leadership role for a practitioner-turned-strategist who combines deep architectural expertise with the commercial acumen to build and scale a world-class Data & AI practice. As Global Head of Data & AI Practice, you will own the front-end remit of the practice worldwide: P&L accountability, offering creation, go-to-market execution, customer advisory and consulting, thought leadership, and strategic partnerships. You will be a close and influential partner to delivery leadership, ensuring offerings are grounded in delivery reality and that clients receive a seamless experience from pursuit through to outcome. You will unify regional presales functions (Americas, Europe and India) under a coherent global strategy and serve as Prodapt''s most senior Data & AI voice with clients.

Reporting Structure & Scope

Direct Reports:

• Americas Presales Leader(s) (Data Modernisation & Platforms) — Canada based
• India-based Presales Team — supporting global pursuit and solutioning activity
• EMEA Presales Leader(s)

Functional Accountability (Owned):

• Global Data & AI Practice P&L — revenue, margin, and growth targets
• Offering portfolio, pricing strategy, and competitive differentiation
• GTM motions across all verticals and geographies
• Customer advisory and consulting — C-suite advisory engagements, strategic assessments, and solution origination
• Partner alliances and co-sell ecosystems (hyperscalers, ISVs, data platform vendors)

Key Working Relationships:

• Global and Regional Delivery Leaders — close partnership to shape delivery models, resolve escalations, and embed offerings into delivery practice
• Prodapt Sales Leadership — pipeline generation, deal qualification, and pursuit strategy
• CTO / Technology Office — alignment on innovation agenda and technical standards

Key Responsibilities

1. Global P&L Ownership & Business Growth

• Own and drive the global Data & AI Practice P&L — revenue, bookings, margin, and pipeline health.
• Define multi-year growth strategy and annual operating plans aligned to Prodapt''s global ambitions.
• Set revenue targets across geographies (Americas, EMEA, APAC/India) and hold regional leads accountable.
• Identify and pursue large-deal opportunities ($10M–$100M+) in partnership with sales, presales, and delivery leadership.
• Build the business case and investment rationale for new capability areas, white-space markets, and adjacent offerings.

2. Offering Creation & Portfolio Management

• Design, own, and continuously evolve the global Data & AI offering portfolio — covering data modernisation, cloud data platforms, AI/ML engineering, Generative AI, Agentic AI, LLMOps, and AI infrastructure.
• Build differentiated, industry-tuned solutions for Telco, Media, Life Sciences, Banking, and other key verticals.
• Translate architectural innovation into commercially packaged offerings — with defined scope, commercial model, and reference customer stories.
• Define pricing frameworks, commercialisation strategies, and deal-shaping playbooks for the practice.
• Maintain a live competitive intelligence view and evolve offerings ahead of market shifts.
• Own the development of reusable accelerators, reference architectures, and solution frameworks that underpin presales quality and accelerate delivery ramp-up in collaboration with delivery teams.

3. Go-To-Market (GTM) Strategy & Execution

• Define and execute integrated GTM strategies across all geographies, verticals, and partner channels.
• Work closely with the Americas Presales Leader and India Presales Team to align solutioning, pursuit, and pipeline generation.
• Champion deal shaping and solution strategy for marquee and strategic pursuits globally — providing senior architectural and commercial oversight.
• Establish and govern the global presales operating model: qualification frameworks, win strategies, proposal quality, and conversion metrics.
• Drive demand generation through executive engagement, industry events, partner ecosystem activities, and digital channels.
• Ensure GTM execution is grounded in real buyer insight — engaging directly with CDO, CIO, CTO, and Chief AI Officer stakeholders.

4. Thought Leadership & Market Positioning

• Establish Prodapt as a recognised Data & AI authority — through published POVs, whitepapers, analyst engagements, conference keynotes, and media contributions.
• Lead and participate in C-suite advisory sessions, industry roundtables, and executive workshops globally.
• Build and maintain a personal profile as a credible, practitioner-level thought leader in enterprise AI, data modernisation, and agentic/generative AI.
• Translate emerging technologies (Lakehouse, Data Mesh, AI Agents, Sovereign AI, FinOps for Data) into actionable enterprise narratives.
• Represent Prodapt at flagship industry events (Gartner Data & Analytics, Databricks Summit, Snowflake Summit, AWS re:Invent, etc.).

5. Strategic Partnerships & Alliances

• Own and develop strategic alliances with hyperscalers (Microsoft Azure, AWS, Google Cloud Platform) and data platform leaders (Databricks, Snowflake, dbt Labs, Fivetran, etc.).
• Negotiate and manage partnership tiers, co-sell agreements, and joint GTM programmes with key technology vendors.
• Leverage partner ecosystems to expand market reach, co-develop solutions, and access joint funding (MDF, co-sell, POC credits).
• Build relationships with Gartner, Forrester, and other analyst firms to shape market perception and influence evaluation shortlists.
• Identify and evaluate acquisition targets, investment opportunities, or white-label partnerships that accelerate practice scale.

6. Customer Advisory & Consulting

• Own Prodapt''s Data & AI advisory and consulting function — acting as the most senior practitioner voice in client-facing strategic engagements.
• Lead executive-level advisory sessions with CDO, CIO, CTO, and Chief AI Officer stakeholders across key accounts and prospect organisations.
• Conduct structured Data & AI maturity assessments, strategic roadmaps, and transformation blueprints as named advisory engagements.
• Originate new opportunities through advisory-led consulting relationships — converting strategic conversations into qualified pursuits.
• Define and standardise Prodapt''s consulting methodology for Data & AI — frameworks, assessment tools, discovery workshops, and CXO presentation standards.
• Serve as executive sponsor on strategic client relationships, providing continuity and credibility from advisory through to delivery handoff.
• Build a small, senior advisory bench capable of conducting high-quality CXO engagements independently across regions.

7. Practice Development & Team Leadership

• Build and lead a globally distributed, high-performing Data & AI GTM team — covering presales, advisory, architecture, and offering management functions. Delivery teams are not in scope.
• Establish a culture of innovation, continuous learning, and technical excellence across all practice layers.
• Drive capability development across Generative AI, Agentic AI, cloud data platforms, data engineering, and AI ethics/compliance.
• Develop clear career pathways and talent management frameworks for Data & AI advisory and presales professionals globally.
• Work in close partnership with Delivery Leadership to ensure offerings are backed by scalable, repeatable delivery models and that client commitments are achievable.
• Mentor senior architects, presales leaders, advisory practitioners, and emerging practice talent.

8. AI & Data Innovation

• Stay ahead of the curve on enterprise AI innovation — Generative AI, Agentic AI, LLMOps, AI compute infrastructure, and Sovereign AI.
• Define Prodapt''s innovation agenda for Data & AI: incubate new solution ideas, sponsor internal R&D, and validate with early adopter clients.
• Develop frameworks for responsible AI, AI governance, ethics, and compliance (GDPR, EU AI Act, sector-specific regulation).
• Leverage hands-on architectural insight to stress-test offerings, review high-stakes solution designs, and provide technical credibility in client engagements.

Required Skills & Experience

1. Leadership & Commercial:

• 15+ years in Data & AI / Technology, with at least 5 years in a senior practice leadership or P&L ownership role.
• Proven track record of building and scaling Data & AI practices in a consulting, systems integration, or managed services environment.
• Experience managing a global team across multiple geographies with direct reports in at least two regions.
• Demonstrated success in winning large-scale transformation programmes ($10M–$100M+) and advising clients through complex data and AI transformation journeys.
• Strong commercial instincts: business development, deal shaping, pricing, margin management, and pipeline discipline.

2. Hands-On Technical Foundation (Essential):

• Prior hands-on career as a Data Architect, Enterprise Architect, or Solutions Architect is strongly preferred — practitioner credibility is a key differentiator for this role.
• Deep expertise in modern data platform architectures: Lakehouse, Data Mesh, Data Warehouse modernisation (Teradata/Oracle/Netezza to Snowflake/Databricks/BigQuery).
• Solid understanding of cloud data platforms: Microsoft Azure (Fabric, Synapse, ADLS), AWS (Redshift, Glue, Lake Formation), Google Cloud Platform (BigQuery, Dataproc, Dataplex).
• Strong working knowledge of AI/ML engineering, MLOps, LLMOps, Generative AI, and Agentic AI frameworks.
• Familiarity with data governance tooling: Unity Catalog, Alation, Collibra, Purview, Snowflake governance, or equivalent.
• Ability to review, challenge, and guide architectural decisions on complex programmes without being a bottleneck.

3. GTM & Offering:

• Proven experience creating commercial offerings, go-to-market programmes, and sales plays for data or AI services.
• Track record of building and operationalising presales functions — from qualification through to proposal and contract.
• Experience managing hyperscaler and ISV partnerships (preferred: Microsoft, Databricks, Snowflake, AWS).
• Demonstrated thought leadership: published content, public speaking, analyst interaction, or executive advisory.

Preferred Qualifications

• Advanced degree in Computer Science, Engineering, Data Science, or a related field.
• Certifications in Enterprise Architecture (TOGAF, ZACHMAN), Cloud (Azure Expert, AWS SA Pro, Google Cloud Platform Professional Data Engineer), or AI/ML platforms.
• Recognised industry thought leader with a public profile in enterprise AI and data transformation.
• Prior experience in Telco, Media, or Connectedness-adjacent industries is a strong differentiator.
• Familiarity with responsible AI frameworks, EU AI Act compliance, and sovereign AI considerations.
• Experience with agentic AI architectures, LLMOps platforms, and AI compute infrastructure (GPU-as-a-service, sovereign AI clusters).