Director, Data & Analytics - Corporate Services
Graham
- Calgary, AB
- Permanent
- Full-time
- Lead the Data & Analytics function, including Data Engineering and Analytics & Visualization
- Own the enterprise Data & Analytics roadmap, delivery model, and budget
- Establish a clear operating model for how analytics demand is managed, prioritized, funded, and delivered
- Improve speed, predictability, and transparency of delivery
- Establish accountability across the organization for data, definitions, and outcomes, with IT as an enablement partner
- Reduce complexity and duplication across data sources through pragmatic architecture and governance
- Build trust with senior leaders and business leaders by delivering insights that directly support operational and financial decisions
- Develop managers and senior technical leaders who can execute independently and consistently
- Define and own the enterprise Data & Analytics strategy and roadmap, aligned to business priorities and value realization
- Design and implement a scalable delivery that supports iterative delivery without constant re-prioritization or failure
- Establish clear roles, responsibilities, and decision rights between IT, Data & Analytics, and business stakeholders
- Enable insights that drive actionable results to improve areas of the business
- Balance central standards with federated execution where appropriate
- Act as a senior partner to executive and operational leaders to clarify business outcomes before solutions are built, establish data ownership, stewardship, and accountability in the business and set realistic expectations on scope, timelines, and trade-offs
- Introduce structured approaches to demand intake, prioritization, and backlog management
- Establish ways of working that shift focus from the status quo to outputs and outcomes that drive enterprise business value
- Ensure analytics initiatives are explicitly tied to business outcomes, not just reports or dashboards
- Lead leaders: coach and develop managers to plan, execute, and deliver consistently
- Improve estimation, dependency management, and delivery forecasting
- Ensure solutions are production-ready, supported, and adopted—not just delivered
- Provide pragmatic leadership across a complex, multi-platform data environment (Azure Data Lake, Databricks, SAP S4/HANA, Power BI, MS Fabric)
- Partner with Enterprise Architecture to reduce unnecessary complexity, establish clear platform usage patterns and guardrails, and guide platform evolution based on business value, not vendor trends
- Establish and mature data governance, quality, and standards in a way that enables, not blocks, delivery
- Introduce consistent definitions, metrics, and master data practices for critical business domains
- Increase confidence in analytics outputs across the organization
- Build a high-performing Data & Analytics leadership team
- Develop technical talent while reinforcing business thinking and accountability
- Foster a culture of continuous improvement, learning, and ownership
- Own the Data & Analytics budget, including platforms, tools, and external partners
- Ensure spend is aligned to outcomes and value realization
- Manage strategic vendor and partner relationships
- 10+ years in Data, Analytics, or Business Intelligence roles, including senior leadership
- Proven experience maturing a data & analytics organization in a complex, multi-business environment
- Demonstrated success improving delivery speed and predictability, business partnership and trust, and data ownership and accountability
- Experience operating in environments with competing priorities and constrained capacity, multiple data platforms and sources, and many organizational changes initiatives occurring simultaneously
- Strategic thinker who can translate vision into executable plans
- Strong executive presence and credibility with senior leaders
- Comfortable challenging business partners constructively
- Able to lead leaders, not just individual contributors
- Strong understanding of:
- Data engineering, analytics, and visualization
- Modern cloud data platforms and architectures
- Agile and iterative delivery models
- ERP experience required; SAP experience is a strong asset
- Experience with Power BI and enterprise analytics platforms required
- AI/ML experience is beneficial but not the primary focus
- Degree in Computer Science, Engineering, Analytics, Business, or related field