MINIMUM QUALIFICATION REQUIREMENTS

Education and Experience:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or an equivalent combination of education, training and experience.
• 10+ years of experience in data management, data warehousing, or related field.
• 5+ years of experience managing a team.
• Master’s degree in Data Science and/or Mathematics would be considered an asset.
• Experience with cloud-based infrastructure and related technology such as Azure.
• Experience with data integration, orchestration, transformation, data modeling, data layer security, object oriented security models and integration with Azure AD.
• Experience with data science, machine learning, and AI technologies.
• Experience with data architecture and strategic solutions with awareness of best practices associated with data lakes, data warehousing and data hubs.
• Experience with DataOps or DevOps methodologies
• Experience in strategic technology planning and execution.

Knowledge, Skills, and Abilities:

• Knowledge of data management, data science, and data security.
• Knowledge of industry best practices and trends in data enablement
• Knowledge of DevOps delivery models and their implementation for data and analytics (DataOps).
• Strong leadership and communication skills both written and verbal.
• Ability to create a fair and equitable environment.
• Ability to lead teams and deliver solutions.
• Ability to problem-solve and to understand new business models and domains.
• Ability to influence others effectively and positively in a team-oriented, collaborative environment.
• Ability to manage multiple projects and priorities.
• Ability to foster and support professional development of team members and guide career planning conversations to set them up for success.
• Ability to create collaboration amongst component teams and motivate towards a common goal.
• Ability to work under pressure and manage multiple priorities with a keen sense of accountability and commitment to end-user advocacy.
• Ability to establish and maintain effective working relationships with a variety of internal and external contacts and team members to provide advice, information, and assistance.
• Ability to translate among the languages used by executive, business, IT, and stakeholders

Where operationally appropriate and subject to change, the City of Vancouver has a Flexible Work Program. This program allows staff to work a hybrid work week from locations that are a daily commutable distance from their work at a City worksite. At this time this position is eligible to be part of the Flexible Work Program
Business Unit/Department: IT, Digital Strategy & 311 (1070)
Affiliation: Senior Exempt
Employment Type: Regular Full Time
Salary Information: Pay Grade RNG-111: $125,619 to $165,280 per annum

MAIN PURPOSE AND FUNCTION

The Manager, Data Enablement is responsible and accountable for the delivery and ongoing management of a new cloud-based data management solution which provides cleansed, organized, curated, and consumable data across all City of Vancouver data domains.
The Manager is also responsible for supporting the Technology Leadership Team (TLT) in executing strategic initiatives such as the implementation and ongoing management of an Innovation Lab which will explore the use of ML/AI and Data Science, implementation and ongoing management of a full Integrated Data Platform, Master Data Management and Data Integration Services.

SPECIFIC DUTIES/RESPONSIBILITIES

Data Engineering and Solution Architecture:

• Creates, manages and implements a data operating model that leverages DevOps and DataOps methodologies.
• Manages the development and implementation of data engineering and solution architecturefor the City of Vancouver.
• Develops and manages the ongoing technical strategy, capability framework, for Data Architecture in partnership with the Enterprise Architecture team.
• In partnership with the Director, Enterprise Data, Analytics and AI, and Enterprise Architecture designs, implements, and manages the data architecture and management of the City’s data ecosystem, ensuring that all data and technology systems are up-to-date, secure, and in compliance with relevant regulations.
• Develops, implements, and manages data governance technology that supports the processes and procedures managed by the Analytics Enablement team.
• Identifies opportunities to leverage data to drive value and work with Analytics Enablement and City Departments to implement these strategies.
• Plans, develops and implements improvements to enhance data quality and accuracy using technical solutions.
• Identifies and evaluates new data engineering and solution architecture technologies that can be used to drive value for the City.
• Develops the three (3) year roadmap for the data lakehouse and associated technologies.
• In partnership with Enterprise Architecture designs and develops standard patterns for data delivery through the data lakehouse and associated technologies such as Fabric, Databricks, Data Factory, Informatica, and others.
• Communicates with stakeholders at all levels of the organization regarding data engineering and solution architecture initiatives.

Data Enablement Technology

• Ensures the integrated data platform can effectively execute on data management processes such as integration, orchestration, transformation, data modeling, data layer security, and object oriented security.
• Designs, develops, implements and governs self-service strategies for business users in the data lakehouse.
• Implements, manages, and governs the medallion architecture for the data lakehouse.
• Implements, manages, and governs the dimensional data model in the data lakehouse.
• In partnership with Analytics Enablement Data Governance team, implements the canonical data model in the data lakehouse
• In partnership with the Enterprise Architecture and Integration team develops, manages and implements the data integration strategy.
• Designs, develops, implements, manages and governs the enterprise data services hub.
• Designs, develops, implements, manages and governs data observability and telemetry solutions for the data lakehouse
• Develops and maintains data pipelines and data lakehouse.
• Ensures that all data and technology systems are up to date, secure and in compliance with relevant regulations.
• Manages the deployment of machine learning models and algorithms.
• Identifies and evaluates new data enablement technologies that can be used to drive value for the City.
• Ensures that all data and technology systems are up-to-date, secure, and in compliance with relevant regulations.
• Communicates with stakeholders at all levels of the organization regarding data enablement technology initiatives.

Data Science, Machine Learning, and AI Infrastructure

• Works with Artificial Intelligence team to develop, test, and deploy models and algorithms.
• In Partnership with the Infrastructure & Operations systems team builds, manages, and maintains the AI infrastructure.
• In partnership with the Artificial Intelligence team and Enterprise Integration team monitors load balancing through Azure APIM for AI models.

Management and Leadership

• Manages a team of five to seven resources.
• Manages the recruitment process and facilitate new employee onboarding.
• Oversees performance management and provide coaching and feedback to support employee growth.
• Maintains effective communication with employees and address any performance or conduct issues in a timely and professional manner.
• Manages relationships with external consulting firms, vendor partners, and contractors relevant to the delivery of the data lakehouse.
• Provides leadership, guidance, and mentoring to team members, fostering and supporting their professional development and guiding their career planning conversations to set them up for success.

Other duties as assigned.