Ritchie Bros. is seeking a Director of Data Engineering & Data Science Engineering to lead a critical function at the intersection of data, analytics, machine learning, and business transformation. This role involves defining and driving the vision for data engineering and data science capabilities to support business growth and operational excellence.
Responsibilities:
- Lead the Data Engineering and Data Science Engineering function for IAA, setting technical vision, delivery strategy, and operating rhythm
- Build and evolve scalable data platforms, BI architecture, and ML-enablement capabilities using the Azure data and analytics stack
- Drive strategy and execution across Microsoft Fabric, Synapse, Power BI, Azure BI technologies, and modern cloud data platforms
- Partner with business and functional leaders to solve high-value problems across Operations, Sales, Marketing, Product, and other key areas
- Guide the design and implementation of robust pipelines, semantic models, dashboards, self-service analytics, forecasting solutions, and machine learning systems
- Help shape the roadmap for advanced analytics, predictive modeling, experimentation, and AI-driven insights
- Mentor, coach, and grow data engineering and data science talent while raising the technical bar across the team
- Establish strong engineering practices across architecture, delivery quality, scalability, governance, and operational excellence
- Collaborate closely with engineering leaders and cross-functional teams to ensure data and AI solutions are aligned with platform, product, and business priorities
- Act as a senior thought partner to leadership on data strategy, technical tradeoffs, and investment priorities
Requirements:
- Proven experience leading Data Engineering, BI, Analytics, and/or Data Science Engineering teams at the Director level or equivalent
- Deep expertise in the Azure BI / data technology stack, including: Microsoft Fabric, Azure Synapse Analytics, Power BI, Broader Azure data and analytics services
- Strong understanding of data engineering architecture, modern analytics platforms, and scalable data pipelines
- Strong foundation in data science, machine learning, and model operationalization
- Demonstrated ability to solve complex business problems through data, analytics, and technical leadership
- Strong mentoring, coaching, and people leadership skills with experience growing high-performing technical teams
- Excellent communication and stakeholder management skills; able to work effectively with a wide range of technical and non-technical partners such as Ops, Business, Sales, Marketing, Product, Engineering
- Ability to operate successfully in a fast-paced, high-visibility environment with multiple priorities and stakeholders
- Strong executive presence and the ability to connect technical decisions to business outcomes
- Experience supporting enterprise use cases across operations, commercial functions, and product-driven organizations
- Experience driving both BI modernization and data science / ML adoption within the same organization
- Familiarity with cloud-native engineering practices, production-grade data platforms, and secure, scalable AI/ML environments
- Experience leading organizations that combine data engineering, analytics engineering, BI, and data science under one leadership model