Sr. Director, Enterprise Data and AI Platform
Ceridian View all jobs
- Canada
- Permanent
- Full-time
- Lead and grow a global data and AI engineering team
- Set strategy for enterprise data architecture and engineering
- Oversee execution of large-scale, complex data initiatives
- Lead platform selection, POC, and buildout of Agentic AI capabilities
- Define long-term AI strategy and drive innovation
- Build and Lead the AI Platform COE
- Oversee the design, development, and deployment of machine learning models and AI solutions that address key business challenges.
- Design and manage Azure-based data platforms (Data Lake, Synapse, Data Factory, Data Fabric)
- Own data pipeline, data product, and asset delivery
- Align platform architecture with business goals and roadmaps
- Partner with business leaders to enable data-driven decisions
- Support advanced analytics, ML, and real-time enterprise reporting
- Define and enforce data governance and security practices
- Ensure data availability, protection, and SLA performance
- Participate in architecture governance (ARB) and enterprise IT strategy
- Manage platform budgets and third-party vendor relationships
- Expertise in modern data stack and infrastructure: Azure Cloud, Data Lake/Warehouse/Mesh, Data Fabric, data integration tools, Power BI, Tableau.
- Proven leadership of Data & ML Engineering/Analytics in global environment.
- Deep understanding of ML operations (MLOps) practices, including model monitoring, retraining, and lifecycle management.
- Strong expertise in machine learning techniques, statistical modeling, and AI technologies, with hands-on experience in deploying models at scale
- Hands-on experience with AI techniques such as natural language processing, computer vision, and deep learning (e.g., PyTorch, TensorFlow, Hugging Face).
- Experience building cross-functional enterprise data warehouses for business analytics.
- Strong background in AI/ML technologies, with familiarity in Agentic AI platforms such as Replit, Vercel etc
- Knowledge of Agile methodologies, particularly SAFe (Scaled Agile Framework).
- Demonstrated ability to manage complex projects, budgets, and vendor relationships.
- Strong business partnership and change management skills.
- Skilled at cross-functional collaboration and aligning delivery with enterprise priorities.
- Advanced degree in computer science, data science, machine learning, or a related field is a plus.
- 10+ years of experience in Enterprise data and AI leadership roles.