Senior Manager, Data Analytics

Walmart•Mississauga, ON

3d•$109,400 - $150,480•Onsite

About The Position

The Senior Manager, Data Analyst (IC) supports the Canadian Technology Data Engineering team by leading complex analytics initiatives end to end—translating ambiguous business problems into actionable, data driven solutions and measurable outcomes. This role partners with technical and business stakeholders to define the “right questions,” ensure trusted data sources, and deliver insights through scalable reporting, automation, and storytelling.

Requirements

Bachelor’s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Engineering, Economics) or equivalent practical experience.
Strong experience in Retail (Brick & Mortar and eCommerce) and as a Data Analyst (12+ years)
Advanced analytics experience building insights and automation using SQL plus a scripting language (e.g., Python/R).
Strong experience presenting to senior stakeholders.
Demonstrated experience establishing/leading data quality and governance practices in partnership with stakeholders.

Nice To Haves

Experience with GCP / BigQuery and working across disparate data platforms.
Experience with hypothesis testing, statistical inference, predictive/prescriptive analytics, and/or experimentation.
Experience standardizing metrics definitions and improving “single version of truth” reporting across teams.
Experience with Generative and Agentic AI

Responsibilities

Lead discovery with stakeholders to clarify problem statements, define success measures, and translate needs into analytical approaches and deliverables.
Translate complex requirements into analytical, data, or mathematical solutions; select methods and tools appropriate to context and constraints.
Drive clarity on trusted data sources and data definitions to improve consistency and reduce rework across teams.
Identify and evaluate internal/external data sources; implement repeatable approaches for acquiring and integrating data, ensuring accuracy, completeness, and accessibility.
Plan and lead efforts to improve data quality and integrity; define, monitor, and remediate data quality metrics and issues.
Coordinate and support security measures to safeguard information against accidental or unauthorized modification/disclosure.
Manage multiple concurrent initiatives by developing plans, defining performance measures, monitoring progress, and adapting approaches.
Partner closely with Data Engineering, Solution Architecture, Quality Automation Specialists (and related functions) to ensure analytics outputs are reproducible, well‑documented, and scalable.
Mentor and lead analysts/engineers informally via standards, templates, reviews, and knowledge sharing—without direct managerial accountability.
Communicate complex analysis in clear business terms; influence stakeholders with evidence and practical examples of solution value.