Undergraduate degree in Data Science, AI, Computer Science, Business Administration, or related field.
5-10 years of experience in data governance, stewardship, modeling, architecture, and master/metadata management.
Proven experience leading enterprise Snowflake platforms and engineering teams.
Familiarity with change management and promoting data practices adoption.
Proficient in analytics and visualization tools like Power BI, Tableau, or Looker.
Strong strategic thinking and communication skills.
Ability to align data initiatives with business objectives.
Responsibilities
Develop and maintain a comprehensive data engineering strategy.
Partner with teams to scope data requirements and build scalable solutions.
Promote adoption of data engineering tools and standards.
Manage and develop data services staff.
Define data engineering requirements and coordinate delivery responsibilities.
Establish data engineering standards and reusable development practices.
Guide data quality and engineering issue resolution processes.
Benefits
Hybrid work model requiring in-office presence two days a week.
Opportunity to lead and shape enterprise data platforms.
Engagement with cross-functional teams for collaborative projects.
Focus on continuous improvement and innovation in data engineering.
Professional development opportunities in data governance and analytics.
Full Job Description
Job Description CoreFactor is searching for a Manager, Data Platforms on a permanent/full-time basis for a client in the GTA.
This position is hybrid and will require the successful incumbent to be in the office two (2) days per week.
Job Purpose
Develop, execute and maintain a comprehensive enterprise data platform strategy and capabilities to support the secure, scalable and governed use of enterprise data across Hydro One. Lead the planning, design, delivery, operation and continuous improvement of enterprise data platforms, including Snowflake, cloud data services, data engineering and reusable enterprise data products.
Duties and Responsibilities
Develop, execute and maintain a complete data engineering strategy and capabilities.
Partner with cross-functional teams to scope data requirements and build scalable data engineering solutions.
Facilitate, educate and promote adoption of data engineering tools, standards, processes and procedures.
Manage, support and develop data services staff.
Coordinate and define data engineering requirements, priorities and delivery responsibilities across business and technology teams.
Establish data engineering standards, reusable patterns and development practices.
Guide and facilitate data quality, pipeline and engineering issue resolution processes.
Provide leadership on data engineering best practices, data quality and performance measures.
Communicate data engineering strategy, standards, patterns and procedures across the organization.
Enforce compliance with internal data engineering, architecture, security and data governance standards and procedures.
Data Architecture
Support cross-functional teams in defining data structures, storage needs and data movement requirements.
Establish and maintain enterprise data architecture standards, patterns and models to support scalable, consistent and reusable data solutions.
Data Analytics
Define and analyze information required for business decisions, including benchmarking.
Perform fit-gap analysis of decision-support data.
Evaluate data quality, accuracy requirements and ongoing quality metrics.
Manage analytics training and adoption activities with change management support.
Requirements
Undergraduate degree in Data Science, Artificial Intelligence, Computer Science, Business Administration or a related field.
5-10 years of experience in data governance, data stewardship, data modelling, data architecture, and master/metadata management.
Experience with change management and driving adoption of data practices.
Strong experience leading enterprise Snowflake platforms and engineering teams, including platform strategy, architecture, data engineering, governance, reliability and optimization
Proficiency with Power BI, Tableau, Looker or similar analytics and visualization tools.
Strong strategic thinking, communication, training and problem-solving skills.
Ability to align data initiatives with business objectives.
Ability to coordinate across multiple departments and manage collaboration.
