Time Type:Regular
Job 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 & ResponsibilitiesCapability 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
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-HybridLocation :Montréal, QC
Company :Cogeco Communications Inc.
