Director, Data Foundations, Automation & Infrastructure

Role overview

Strategy and data architecture

• Define and deliver the Data Foundations strategy and roadmap aligned with business, CDAO, and enterprise priorities.
• Design and maintain architecture and models for curated, master, and reference data assets.
• Establish standards for modeling, naming, metadata, integration, and data sharing.

Development and operations

• Lead the design, development, and operation of ETL processes and data pipelines.
• Ensure recurring production is accurate, timely, reconciled to authoritative sources, and within published service levels.
• Monitor data flows, resolve issues, and drive root-cause remediation.
• Embed data quality checks, validation, and controls throughout the data lifecycle.
• Protect data from loss or unauthorized access in line with legal and company standards.

Modernization and enablement

• Adopt technologies and practices that improve scalability, efficiency, and resilience; partner with Technology on platform strategy, infrastructure, and production.
• Prepare and structure data for advanced analytics and AI use cases.
• Manage and prioritize data requests transparently with clear service levels.
• Promote data literacy and self-service through documentation, data dictionaries, and a community of practice.
• Partner with stakeholders on data definitions and downstream impacts, and with Data Governance on quality, metadata, lineage, and risk requirements.

Applications and people leadership

• Oversee business-managed applications from intake and design through delivery, enhancement, and ongoing support, ensuring controls and alignment with technology, data, and risk standards.
• Build and develop a high-performing team, work effectively with vendors, set goals and accountability, and coach for growth and continuous improvement.
• Attract, retain, and develop talent; model BMO values and foster an inclusive culture.
• Apply the Risk Management Framework, make informed decisions, protect assets, and follow policies, laws, and regulations.

Qualifications

• At least 9 years in data management, data engineering, or a related field, including leadership of data teams.
• Deep expertise in ETL, data pipelines, data modeling, and data quality management.
• Strong SQL proficiency and knowledge of modern data programming languages such as Python.
• Experience with cloud and modern data platforms.
• Working knowledge of master data, metadata, semantic layers, data governance, privacy, and integrity.
• Experience in a highly regulated environment; Commercial Banking or financial services experience is an asset.
• Excellent communication and stakeholder management skills.
• Related post-secondary degree or equivalent education and experience.

Leadership attributes

• Treat data as a documented, reconciled, reusable product and build processes that sustain accuracy.
• Balance modernization with dependable production and understand Commercial Banking data across clients, products, and channels.
• Communicate transparently, influence stakeholders, and align teams around shared definitions.
• Thrive in ambiguity and solve complex, interdependent problems.

Compensation

• Posted salary range is $120,000–$215,000; the posting identifies the pay type as salaried.