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Senior Manager, Data Engineering & Data Products
McKesson
Montréal, CAN
Full-time
Mid-Senior
Hybrid
Discovered 1 weeks ago
Data engineeringData integrationData lakesData warehousesData modelingData product delivery
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Role Overview
McKesson Canada is seeking a Senior Manager, Data Hub Engineering & Data Products to lead the evolution of its Enterprise Data Hub service.
The role is accountable for modern data engineering capabilities, trusted data products, AI-enabled engineering practices, and operational excellence across the data lifecycle.
The position combines data engineering, product thinking, Agile delivery, governance, DataOps, innovation, service ownership, and platform evolution.
Key Skills for This Role
Data engineeringData integrationData lakesData warehousesData modelingData product delivery
Full Job Posting
Position Summary
McKesson Canada is seeking a Senior Manager, Data Hub Engineering & Data Products to lead the evolution of its Enterprise Data Hub service.
The role is accountable for modern data engineering capabilities, trusted data products, AI-enabled engineering practices, and operational excellence across the data lifecycle.
The position combines data engineering, product thinking, Agile delivery, governance, DataOps, innovation, service ownership, and platform evolution.
Key Responsibilities
- Lead, coach, and inspire data engineers and technical specialists while building a culture of ownership, accountability, inclusiveness, innovation, and continuous improvement.
- Support workforce planning, recruiting, talent development, succession planning, and performance management.
- Ensure the design, implementation, deployment, and support of enterprise-scale data solutions.
- Drive scalable data ingestion, transformation, quality, semantic, and consumption capabilities.
- Enforce engineering standards, reusable patterns, architecture guardrails, and development best practices.
- Collaborate with business and technology stakeholders and drive innovation through emerging technologies and improved engineering workflows.
- Lead monitoring, observability, incident management, root cause analysis, and continuous service improvement.
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