Data & AI Delivery Leader

As the Data & AI Delivery Leader, you will drive high-impact initiatives that deliver tangible business value through a balanced mix of architectural strategy and hands-on execution. In this role, you will lead the end-to-end delivery of modern data platforms, generative AI, and intelligent automation while collaborating across business and technology teams to shape scalable, secure, and maintainable solutions. Lead architecture and delivery for strategic enterprise Data and AI initiatives in a role that is intentionally hands-on, with direct impact on scalable, secure, high-quality business outcomes. Shape enterprise data foundations, analytics architecture, AI/ML enablement, generative AI, knowledge retrieval, and intelligent automation capabilities. Influence end-to-end solution direction, enterprise standards, and reusable architecture patterns across the organization. Build long-term Data and AI capability across the team and broader organization through mentoring, coaching, reusable playbooks, and practical knowledge transfer. Own end-to-end architecture for Data and AI solutions aligned to enterprise strategy, business goals, and platform standards, while remaining hands-on in key solution areas. Define scalable, secure, and reusable architecture patterns across data ingestion, transformation, modelling, semantic layers, analytics, AI/ML, and generative AI components. Translate business capability needs into architecture blueprints, technical decisions, and implementation direction. Lead delivery execution across product, engineering, governance, security, and business teams from concept through implementation, while maintaining a reasonable percentage of direct involvement in solution shaping and critical execution decisions. Shape new initiatives by defining scope, sequencing, dependencies, risks, assumptions, and high-level estimates. Drive architecture and delivery decisions across multiple concurrent efforts while balancing speed, quality, risk, sustainability, and value realization. Guide data architecture across cloud-native platforms including lake, warehouse, semantic, and consumption layers, and ensure governed, reusable data models aligned to business definitions. Lead design and delivery of enterprise AI solutions including generative AI, retrieval-augmented generation, enterprise AI assistants, knowledge retrieval, intelligent workflow automation, and predictive analytics use cases. Establish practical delivery and evaluation patterns for AI solutions from experimentation through production rollout, monitoring, and continuous improvement. Ensure solutions meet enterprise standards for governance, security, privacy, responsible AI, operational readiness, and supportability. Act as a key interface across business stakeholders, product leaders, governance leaders, engineering teams, and enterprise technology leadership, while actively building team capability through mentoring, coaching, and practical knowledge transfer. Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, Software Engineering, Artificial Intelligence, or a related technical field. 10+ years of experience in solution architecture, data architecture, enterprise data platforms, analytics delivery, AI solution design, or related technology leadership roles. Strong experience leading end-to-end solution design and delivery for complex data, analytics, and AI initiatives in enterprise environments. Deep understanding of cloud data platforms, preferably GCP / BigQuery or equivalent enterprise cloud ecosystems. Strong expertise in data architecture, data modelling, semantic design, analytical solution patterns, and governed data foundations. Practical experience designing or leading enterprise AI solutions, including generative AI, knowledge retrieval, AI assistants, or ML-enabled decision-support capabilities. Ability to balance enterprise data platform thinking with AI solution delivery and business adoption. Experience guiding cross-functional teams across architecture, engineering, analytics, governance, security, and business stakeholders. Strong understanding of data governance, metadata, lineage, quality, security, responsible AI, and enterprise standards. Strong communication, leadership, stakeholder management, and decision-making skills, with the ability to operate effectively in ambiguity and lead through change. Experience supporting enterprise AI assistants, retrieval-augmented generation, knowledge retrieval, or similar Data and AI solution patterns. Experience defining AI governance guardrails, model risk controls, or responsible AI practices in an enterprise setting. Familiarity with metadata, data catalog, governance, vector search, or knowledge platform capabilities. Experience with Git-based delivery practices, DevOps, CI/CD, and modern engineering standards for data and AI platforms. Exposure to domain-oriented data product principles and federated delivery models. Thrive at work and at home.