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Walmart Canada · 4 months ago

Principal, Data Analyst

United States

Full-time

Remote

Senior Level, Lead/Staff

$90K/yr - $180K/yr

7+ years exp

Walmart Canada is seeking a Principal Data Analyst to transform complex workforce data into actionable insights. This role focuses on building intuitive dashboards and AI-powered data products that facilitate self-service and storytelling, enabling leaders to understand the implications of their data.

DeliveryRetailShopping

Responsibilities

Lead Strategic Reporting & Dashboard Development: Design intuitive dashboards (Tableau, Power BI, GCP) that enable self-service, proactively surface insights, and embed trusted logic and context for clarity and consistency

Build Scalable & Reliable Data Foundations: Transform complex data into clean, automated pipelines and collaborate with engineers to deliver dynamic, AI-enhanced reporting experiences

Drive Data Consistency & Alignment: Ensure data reliability by standardizing definitions across teams, resolving disconnects early, and championing governance practices

Tell Stories That Influence: Transform data into clear, compelling narratives through visualization and storytelling, empowering users to understand and act with confidence

Integrate AI for Smarter Insights: Leverage AI to scale insights through features like natural language summaries and anomaly detection, while ensuring clarity, speed, and stakeholder trust

Lead Through Influence: Build trust and drive adoption by connecting across teams, aligning through clarity and storytelling, and influencing decisions without direct authority

Qualification

Data analyticsSQLPower BITableauGCPAI integrationData storytellingData processing toolsCross-functional influenceCommunication skillsTeam collaborationProblem-solving

Required

7+ years in data analytics, BI, or people analytics within large, complex environments

Advanced SQL skills and experience with cloud platforms (e.g., GCP, BigQuery)

Proficient in BI tools like Power BI, Tableau, or similar

Hands-on experience with automation and data processing tools (e.g., Alteryx, Dataiku, Python)

Familiarity with integrating AI features into reporting workflows

Deep understanding of how workforce data informs decisions across HR, Finance, and Operations

Skilled at translating complex data into high-trust insights for planning and strategy

Ability to anticipate downstream impacts and proactively address misalignment

Proven ability to simplify complex analysis for senior audiences

Strong visual storytelling skills—turning dashboards into persuasive narratives

Track record of enabling leaders to act quickly and confidently on insights

Experience navigating matrixed, enterprise-scale organizations

Ability to influence without authority through clarity and evidence

Comfortable setting standards and driving quality in ambiguous environments

Option 1: Bachelor's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Arts, Finance or related field and 4 years' experience in data analysis, data science, statistics, or related field

Option 2: Master's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in data analysis, data science, statistics, or related field

Option 3: 6 years' experience in data analysis, data science, statistics, or related field

Preferred

Experience with HR systems like Workday

Background in workforce planning, HR transformation, or financial headcount planning

Exposure to high-volume, operationally complex environments (e.g., retail, logistics, supply chain)

Data science, data analysis, statistics, or related field

Master's degree in Business, Computer Science, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field

Related industry experience (for example, retail, merchandising, healthcare, eCommerce)

Successful completion of assessments in data analysis and Business Intelligence tools and scripting languages (for example, SQL, Python, Spark, Scala, R, Power BI, or Tableau)