Delivery Lead

Why this role exists: The Delivery Lead drives the end-to-end delivery of complex data and AI initiatives across the Officeworks technology landscape, ensuring that roadmap sequencing and technical execution across Snowflake, source-of-record systems, and cloud platforms are aligned with business priorities. This role requires significant engagement and orchestration capabilities, working closely between business SMEs and Technology teams to manage demand, balance resource capacity, and coordinate multi-disciplinary project work. This role supports the Technology function to transition toward a democratised, self-serve analytics model by providing a seamless, collaborative interface between engineering teams and business stakeholders. It plays a critical part in the execution of the enterprise data strategy, helping Officeworks plan, prioritise, and realise the value of its investment in AI and modern data platforms. Where you will make a difference: In this role you will: End-to-End Delivery Management & Planning: - Lead the execution and detailed delivery planning of data and AI workstreams from inception through to operational handover. - Orchestrate and manage the integration of Snowflake-based solutions with source-of-record systems and cloud infrastructure. - Coordinate and track project work to ensure delivery remains aligned with the SAP BW migration and Data Sphere transition requirements. Roadmap, Sequencing & Resource Orchestration: - Partner with stakeholders across all levels to orchestrate, structure, and communicate the clear prioritization of initiatives. - Map, track, and mitigate technical and resource dependencies across multiple domains to safeguard critical delivery timelines. - Balance and align the competing demands of new AI projects with foundational data engineering and technical debt requirements against available team capacity. - Develop, refine, and manage the integrated delivery roadmap across data domains, acting as the primary point of alignment for delivery schedules. Stakeholder Collaboration & Demand Prioritization: - Drive tight alignment between business units and engineering teams to ensure functional and non-functional requirements are transparently captured and planned. - Actively collaborated with business SMEs and technology leads to translate business requirements into structured technical sprint plans and achievable delivery schedules. - Facilitate and contribute to prioritisation governance forums to ensure cross-functional alignment and that resources are directed toward highest-value initiatives. Process & Continuous Improvement - Identify opportunities to optimise delivery workflows, agile ceremonies, and cross-team processes to improve velocity, coordination, and quality. - Drive the adoption of improved documentation standards and IP capture processes to ensure long-term sustainability of the data function. - Continuously review and refine delivery frameworks, ensuring they adapt to the specific operational needs of AI and machine learning lifecycles. Stakeholder Alignment & Governance - Drive alignment between business units and engineering teams to ensure functional and non-functional requirements are met. - Contribute to prioritisation governance forums to ensure resources are directed toward highest-value initiatives. Risk & Financial Stewardship - Govern project risks, delivery bottlenecks, budgets, and partner engagements to ensure high-quality outcomes within financial parameters. - Monitor delivery velocity and resource capacity, ensuring standards are maintained during the transition to permanent team models. Strategic Alignment - Ensure all delivery planning and execution activities reinforce the enterprise data strategy and the move toward data democratisation. - Partner with the Data Architect and Technical Associate Managers to ensure planned technical solutions are scalable, sustainable, and aligned with engineering capacity. Who you will be working with: - Technology Teams: Partner closely with Data Architects, Technical Associate Managers, and AI Engineers to coordinate technical execution, clarify dependencies, and track delivery points. - Business Stakeholders: Collaborate with functional leaders and business SMEs to translate business-led requirements into technical delivery plans, managing expectations around prioritisation and timelines. - Data Leadership: Work with the Data Platform Manager and Enterprise Data Architects to align resource allocations and delivery roadmaps with broader strategic goals. What success looks like: - Execution & Delivery Excellence: Delivery of prioritised roadmap items on time, within budget, and to the agreed technical specification through disciplined resource and sprint orchestration. - Stakeholder Alignment & Confidence: High levels of trust, collaboration, and consensus between the business and technology teams regarding priority, capacity constraints, and delivery progress. - Effective Planning & Risk Mitigation: Proactive identification and resolution of delivery bottlenecks, resource contentions, technical dependencies, and commercial risks. - Continuous Improvement: Measurable improvements in delivery efficiency and velocity, with newly established ways of working successfully embedded across teams. - Strategic Consistency: Successful implementation of projects that demonstrably move the needle on data democratisation and self-serve analytics. How you will lead: Individual Contributor - Lives our Officeworks values and behaviours - Proactively contributes to a safe working environment, escalates appropriately if there are unsafe conditions or inappropriate behaviour - Operates in line with applicable Officeworks company policies and Code of Conduct - Demonstrates a strong sense of personal accountability and curiosity to learn and develop Qualifications and work experience: Essential - Education: Tertiary qualifications in Information Technology, Business, or a related field. Certifications in project management and agile are valued. - Experience: Minimum of 8-10+ years in technology delivery management, project management, or scrum master roles, specifically within data-heavy environments (Data Warehousing, Analytics, or AI/ML). - Planning & Orchestration: Proven track record of managing end-to-end delivery roadmaps, project sequencing, sprint planning, and cross-team resource orchestration in agile or hybrid environments. - Stakeholder Management: Exceptional capability to lead cross-functional prioritisation discussions, manage stakeholder expectations, translate business needs to technical plans, and drive consensus. - Technical Knowledge: Demonstrated experience managing delivery and technical dependencies across Snowflake, Cloud platforms (Azure/AWS/GCP), and complex source systems. - Process Improvement: Demonstrated experience in identifying bottlenecks and implementing delivery process improvements within a technology delivery context. Preferred - Transformation Exposure: Experience supporting large-scale data migrations (e.g., SAP BW/Data Sphere transitions). - Industry Context: Experience within the Retail or FMCG industry, particularly in an omnichannel environment. - Continuous Improvement Methodologies: Familiarity with Lean, Six Sigma, or similar continuous improvement frameworks is highly desirable.