Our culture lifts you up—there is no ego in the way. Our common purpose? We all want to win for our customers. We aim to always be evolving, dynamic, and ambitious. We believe in the power of genuine connections. Each employee is a part of what makes us unique on the market: agile and dedicated.
Time Type:RegularJob Description :Overview of the RoleThe Data & Analytics Crew Lead (Senior Director) occupies a hybrid leadership position that bridges the gap between long-term technical capability and immediate business delivery. This role is uniquely responsible for both "Future-Proofing" the organization's data infrastructure and ensuring that day-to-day data products, insights, and pipelines actively drive commercial success.
The Crew Lead directly connects high-level organizational missions with the execution of the data strategy. You will oversee both the technical excellence and the direct squad deployment across four core data domains: Data Science, Data Engineering, Data Architecture, and Data Analytics. You are simultaneously the architect of the data factory and the director ensuring it delivers high-value outputs to the business.
Tasks & Responsibilities
Capability Strategy & Governance (The Chapter Focus)
Pioneer the 24-Month Data Vision: Define the long-term technical and architectural vision for Cogeco's data ecosystem, ensuring that machine learning, data pipelines, and modeling standards anticipate future market shifts.
Architect Unified Governance: Establish and enforce enterprise-wide data governance, privacy standards, and data quality frameworks to guarantee data consistency, absolute reliability, and ethical compliance across all business units.
Design Repeatable Methodologies: Standardize the fundamental "factory" logic—such as master data management, CI/CD processing pipelines, and BI semantic layers—to eliminate redundant work and technical debt.
Chair the Data & AI Governance Committee: Serve as the permanent Chair of the cross-functional Governance Committee, steering enterprise-wide alignment on data policies, evaluating AI use cases for risk compliance, and prioritizing data infrastructure investments across the business.
Remove Infrastructure Barriers: Actively identify and dismantle systemic bottlenecks, computing constraints, and data silos that slow down your squads’ ability to deliver insights at scale.
Lead Functional Leaders: Manage and coach the individual Chapter Area Leads and Team Leads for Data Science, Data Engineering, Data Architecture, and Data Analytics, guiding them to balance operational output with functional mastery.
Workforce Blueprinting & Hiring: Design the long-term hiring strategy for the data organization. Make final decisions on talent acquisition, onboarding standards, and the use of external contractors vs. internal resource building.
Safeguard Technical Benchmarks: Enforce rigorous technical benchmarks across all business units, ensuring that a specialist meets the same high standard of craft excellence regardless of which squad they are assigned to.
Continuous Upskilling: Anticipate emerging technology trends (e.g., Generative AI/LLM orchestration, advanced MLOps, real-time streaming architectures) and build continuous learning paths to upskill the entire team
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Strategic Delivery & Business Alignment (The Crew Focus)
Drive Commercial Value: Partner directly with business unit executives and product owners to translate commercial goals into a prioritized data roadmap. Ensure that data products actively move business metrics (e.g., customer acquisition, churn reduction, operational efficiency).
Cross-Functional Squad Deployment: Dynamically deploy and embed data scientists, engineers, and analysts into cross-functional business squads, aligning the right technical skills to the highest-priority business initiatives.
Oversee High-Stakes Project Delivery: Serve as the escalation point and strategic director for enterprise-level data initiatives (e.g., migrating to a modern cloud data stack, launching real-time personalization models, or implementing cross-company reporting suites).
Manage the Data Portfolio: Balance the operational trade-offs between urgent, short-term business requests (e.g., ad-hoc commercial dashboards) and long-term infrastructure health.
Skills & Experience
Education: Bachelor’s degree in a technical or quantitative field (e.g., Computer Science, Data Science, Statistics, Information Systems, or Engineering); Master’s degree or MBA is a strong asset.
Domain Expertise: Minimum 10–12 years of experience in the data space, featuring a deep professional literacy across the four core domains: Data Engineering (ETL/ELT, pipeline design), Data Science (predictive modeling, ML execution), Data Architecture (cloud infrastructure, data warehousing), and Data Analytics (BI, executive reporting).
Leadership Experience: Minimum of 10 years in a people-management role, with proven experience navigating matrixed organizations—ideally managing both functional talent and direct project delivery outcomes.
Commercial Acumen: Excellent ability to communicate complex data architectures and AI concepts into clear business cases, financial ROI, and strategic advantages for non-technical stakeholders.
Change & Project Management: Proven track record of successfully delivering large-scale data transformation projects on time, while simultaneously restructuring team workflows and setting technical standards.
Keys to Success
You must be willing to make tough talent and structural decisions. Success in this role requires prioritizing the long-term health of the company over the immediate comfort of the status quo.
The ability to move beyond being a "top practitioner." You must find professional value in building the system that enables others, rather than being the primary expert who solves every problem personally.
Term Impact: Success is found in trading the quick satisfaction of "firefighting" project issues for the lasting influence of designing the rules and frameworks that improve the entire organization.
#LI-Hybrid
Location :Montréal, QCCompany :Cogeco Communications Inc.At Cogeco, we know that different backgrounds, perspectives, and beliefs can bring critical value to our business. The strength of this diversity enhances our ability to imagine, innovate, and grow as a company. So, we are committed to doing everything in our power to create a more diverse and inclusive world of belonging.
By creating a culture where all our colleagues can bring their best selves to work, we’re doing our part to build a more equitable workplace and world. From professional development to personal safety, Cogeco constantly strives to create an environment that welcomes and nurtures all. We make the health and well-being of our colleagues one of our highest priorities, for we know engaged and appreciated employees equate to a better overall experience for our customers.
If you need any accommodations to apply or as part of the recruitment process, please contact us confidentially at [email protected]
Skills Required
- Bachelor's degree in a technical or quantitative field (Computer Science, Data Science, Statistics, Information Systems, Engineering)
- Master's degree or MBA
- 10-12+ years of experience across Data Engineering, Data Science, Data Architecture, and Data Analytics
- Minimum 10 years of people-management experience with matrixed organizations
- Proven track record delivering large-scale data transformation projects (cloud migrations, real-time models, enterprise reporting)
- Deep professional literacy in ETL/ELT, pipeline design, data warehousing, cloud infrastructure, ML execution, and BI/reporting
- Experience defining and enforcing enterprise data governance, privacy, and data quality frameworks
- Ability to translate complex data/AI architectures into business cases and ROI for non-technical stakeholders
- Experience designing hiring strategies, workforce planning, and managing use of contractors vs internal resources
What We Do
Rooted in the communities it serves, Cogeco Inc. is a growing competitive force in the North American telecommunications and media sectors with a legacy of more than 65 years. Through its business units Cogeco Connexion and Breezeline, Cogeco Communications provides Internet, video and phone services to 1.6 million residential and business customers in Québec and Ontario in Canada as well as in thirteen states in the United States. Through Cogeco Media, Cogeco owns and operates 21 radio stations primarily in the province of Québec as well as a news agency. Cogeco's subordinate voting shares are listed on the Toronto Stock Exchange (TSX: CGO). The subordinate voting shares of Cogeco Communications Inc. are also listed on the Toronto Stock Exchange (TSX: CCA).

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