Director, Data, AI, & Automation Services

Bird Construction•Mississauga, ON

About The Position

As a member of the Business Systems leadership team reporting to the Vice President, Business Systems, the Director, Data, AI & Automation Services leads Bird's enterprise data, analytics, AI, automation, and information governance services. The role is accountable for translating business strategy into a practical Data, AI & Automation roadmap that improves decision-making, project and operational performance, productivity, and responsible innovation across Bird. The Director leads the modernization of Bird's data platform and analytics ecosystem, establishes scalable AI and automation capabilities, and advances enterprise data governance, data quality, stewardship, and data fluency. Working with executive sponsors, business leaders, Cybersecurity, Privacy, Enterprise Architecture, and delivery teams, this role ensures data and AI capabilities are trusted, secure, adopted, and measurable in business value.

Requirements

Post-secondary degree in Computer Science, Engineering, Data Science, Information Technology, Business, or a related discipline.
Minimum 10 years of progressive experience in Data, Analytics, Artificial Intelligence, Automation, or Digital Transformation.
Prior Director-level (or equivalent senior enterprise leadership) experience is required.
Demonstrated experience operating at the enterprise leadership level, including partnering directly with executive leadership and cross-functional , influencing strategic decisions, and communicating complex technical concepts in clear business language
Minimum 8 years of leadership experience managing high-performing technical teams.
Proven experience developing and executing enterprise data and AI strategies.
Demonstrated ability to lead organizational change, technology adoption, and enterprise capability-building initiatives , including data literacy, AI fluency, self-service analytics, and responsible AI adoption, across business functions
Strong understanding of Artificial Intelligence, Machine Learning, Generative AI, predictive analytics, and business intelligence.
Deep knowledge of data warehousing, lakehouse architectures, data governance, and enterprise analytics.
Experience with data quality management, master data management, metadata management, and information governance.
Knowledge of AI lifecycle management, responsible AI practices, and modern data engineering methodologies.
Experience building scalable data platforms and self-service analytics capabilities.
Proven ability to embed governance and data fluency practices into analytics delivery, automation initiatives, AI adoption, and business transformation programs.
Experience translating complex data concepts into clear business language for executives, operational leaders, and cross-functional stakeholders.
Ability to promote data fluency across business functions by improving data literacy, self-service analytics adoption, and responsible use of AI-enabled insights.
Strong understanding of data quality, metadata management, master data management, privacy, security, and information lifecycle management.
Demonstrated ability to establish data governance frameworks, stewardship models, data ownership practices, and enterprise data standards.
Strategic thinking and business acumen.
Strong stakeholder management and executive communication skills.
Proven ability to lead organizational change and technology adoption.
Excellent verbal, written, and presentation skills.
Ability to communicate complex technical concepts to technical and non-technical audiences.
Strong problem-solving, decision-making, and organizational skills.

Nice To Haves

Master's degree considered an asset.
Experience leading enterprise AI adoption initiatives.
Experience implementing AI governance and data governance frameworks.
Experience in construction, engineering, or project-based industries is considered an asset.
Knowledge of project delivery methodologies including Agile and Scrum.

Responsibilities

Develop and execute Bird's enterprise Data, AI, Analytics, and Automation strategy, aligned with corporate objectives and the priorities of the Business Systems leadership team, translating business strategy into measurable outcomes across decision-making, operational excellence, and innovation.
Establish and maintain a multi-year roadmap and prioritized portfolio for data modernization, AI adoption, analytics, automation services, and information governance — sequencing initiatives by business value, risk, feasibility, and adoption readiness, and reporting quantified value realization to executive leadership.
Lead the modernization and operation of Bird's enterprise data platform, including lakehouse, Azure Databricks, semantic models, enterprise data models, metadata, data pipelines, and analytics architecture, in partnership with Business Subject Matter Experts, Data Architects, and Business Analysts.
Establish and maintain enterprise standards for analytics, reporting, data engineering, AI solution development, and delivery governance — covering architecture reviews, solution design reviews, testing, release management, training, documentation, and operational support.
Lead enterprise data governance, master data management, data quality, metadata, stewardship, and information lifecycle management, ensuring compliance with privacy, cybersecurity, regulatory, and corporate governance requirements — including ownership of the Semarchy MDM tool and enterprise data standards.
Establish and operationalize responsible AI governance and lifecycle controls for Generative AI, Microsoft Copilot, machine learning, predictive analytics, and intelligent automation — covering AI inventory, human oversight, third-party AI/data risk, monitoring, incident response, and decommissioning, aligned with recognized frameworks such as NIST AI RMF (Govern, Map, Measure, Manage) and ISO/IEC 42001)
Deliver trusted analytics, business intelligence, KPI frameworks, dashboards, predictive models, and AI-enabled solutions — including Power BI visualization on the enterprise Lakehouse — that improve executive, operational, project, and functional decision-making, and leverage structured, unstructured, and IoT data to solve complex business challenges and improve project outcomes.
Lead enterprise automation services and the Automation Center of Excellence, including workflow automation, RPA, AI Agents, reusable patterns and templates, citizen-development guardrails, and consistent benefits realization through KPIs, ROI tracking, and process rationalization.
Champion enterprise data literacy, AI fluency, self-service analytics, adoption, and change management — including Bird's Data & AI Community of Practice and the Data & AI Fluency Journey — measuring and communicating the business value delivered through data, AI, and automation initiatives.
Build, coach, and lead a high-performing Data, AI & Automation Services team across Data Engineers, Data Analysts, Data Scientists, AI Specialists, and Automation professionals, and foster a culture of innovation, continuous improvement, collaboration, and customer service excellence in partnership with executive leadership, Cybersecurity, Enterprise Architecture, Privacy, and business stakeholders.