Senior Insight Analyst
- Canada
The pay range for this position is between $70,400.00 - $79,100.00 · Full-time
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Job details
- Pay
- The pay range for this position is between $70,400.00 - $79,100.00
- Job type
- Full-time
- Apply by
- Experience
- · Experience: 2–4 years for Insights Analyst or 4–6 years for Senior Insights Analyst, in analytics, business intelligence, or a related field.
- Posting language
- English
- Posted
Original job description
Are you someone who thrives on helping others succeed, enjoys making an impact, and takes pride in guiding customers to the right solutions for their projects? If you’re also naturally curious and eager to keep learning, consider starting or growing your career with us at The Home Depot.
Position Purpose: Can you find exactly why a number moved, then explain it to a merchant and an analytics engineer in the same afternoon? That's everyday work for our Decision Analytics team in Finance. We build the data products, scorecards, and AI tools that finance and merchandising leaders across The Home Depot Canada rely on. And we do it in a company built on strong relationships and respect for all people.
In this role, you will own the analytics behind key finance and merchandising decisions, from markdowns and clearance to store performance. You will run complex reporting workflows, advise partners on test design, and turn results into recommendations they act on. We're hiring at the Insights Analyst or Senior Insights Analyst level, depending on experience; senior hires work more independently and lead product ownership. Apply today and help shape the next chapter.
Key Responsibilities and Tasks Key Responsibilities Tasks
Finance and Merchandising Analytics & Decision Support
· Business Rules Ownership: Own the business rules and analytics behind finance and merchandising decisions such as markdowns and clearance.
· Complex Reporting Workflows: Run and maintain the technically complex reporting workflows partners act on, keeping them accurate, documented, and on time.
· Test & Learn Guidance: Advise finance and merchandising partners on how to design their tests, including control selection, duration, and success metrics, so the test and learn methodology answers their objective.
· Performance Measurement & Insights: Build Tableau dashboards and scorecards that connect business decisions to store and financial results, including cost-benefit analysis. Turn the results into recommendations partners can act on.
Data Quality, Automation & AI Innovation
· Root-Cause Troubleshooting: Trace a wrong number back to its cause, fix what's in scope, and hand analytics engineering a clear diagnosis rather than a symptom.
· Workflow Modernization: Move legacy workflows, including Alteryx, to SQL- and Python-based processes in partnership with analytics engineering.
· AI Integration: Use enterprise AI tools such as Gemini, Copilot, and NotebookLM to automate workflows and build AI agents or assistants for partner teams.
Cross-Functional Collaboration & Business Impact
· Product Ownership: Act as the business-side owner for analytics tools, writing requirements and acceptance criteria, validating what analytics engineering builds, and driving adoption.
· Communication: Explain technical issues and their impact in business language that finance and merchandising business partners can understand. Learn how partners use your tools so you can improve them.
Nature and Scope
- Position reports to manager or above.
- This position has no direct reports.
- Typically does not require travel.
Minimum Requirements
Education & Experience
· Education: Bachelor's degree in Business Analytics, Finance, Economics, Statistics, Computer Science, Engineering, or a related quantitative field.
· Experience: 2–4 years for Insights Analyst or 4–6 years for Senior Insights Analyst, in analytics, business intelligence, or a related field. Retail experience is highly beneficial.
· Certifications (Bonus): Relevant certifications are an asset, such as Tableau or Alteryx certifications.
Technical Proficiency
Must-haves apply at both levels; we weigh assets by level and expect senior candidates to bring most of them. Each item is tested, including in a live exercise and a dashboard walkthrough.
· SQL (Must-Have): Writing complex SQL in a cloud warehouse (BigQuery preferred) and finding why a query returns the wrong number.
· Tableau (Must-Have): Building and maintaining dashboards that business users rely on.
· Troubleshooting (Must-Have): Tracing a wrong number to its source and telling data, logic, and business-rule issues apart.
· AI Fluency (Must-Have): Using AI tools daily, checking their output, building with them, and knowing what data stays out.
· Microsoft Office (Must-Have): Using advanced Excel, such as Power Query, XLOOKUP, dynamic array formulas, and scenario models, and building PowerPoint presentations for business partners.
· Python (Asset): Transforming data and automating workflows; reading and explaining others' code.
· Legacy Workflows (Asset): Running, documenting, and migrating workflows built by others; Alteryx experience preferred.
· Requirements (Asset): Writing requirements and acceptance criteria analytics engineers can build from.
· Test Design (Asset): Understanding test-versus-control measurement well enough to advise partners.
Skills & Competencies
- Financial Acumen (Must-Have): Strong understanding of retail financial performance drivers, including comp sales, sales to plan, run rates, margin, and profitability. Connects metrics across the business and can explain underlying performance drivers and trade-offs.
- Business Insight: Applies knowledge of the retail business, market dynamics, and financial performance to identify opportunities, solve problems, and support informed decision-making.
- Consultative Partnership: Influences decisions through insight, curiosity, and constructive challenge while empowering partners to own solutions and outcomes.
- Drives Results: Delivers high-quality outcomes, maintains accountability, and consistently executes against commitments, even in complex or challenging situations.
- Action Oriented: Embraces new opportunities and tackles challenges with urgency, initiative, and a bias for action.
- Collaborates & Communicates Effectively: Builds strong partnerships across functions and communicates clearly and appropriately to diverse audiences, fostering alignment and shared success.
- Customer Focus: Keeps internal and external customer needs at the centre of decisions and delivers solutions that create value.
- Planning & Prioritization: Effectively plans, prioritizes, and aligns work to meet commitments and support organizational objectives.
- Continuous Improvement & Process Optimization: Seeks opportunities to improve processes, eliminate inefficiencies, and enhance effectiveness through continuous improvement.
- Learning Agility & Self-Development: Demonstrates curiosity, learns quickly from experience, and actively pursues opportunities for personal and professional growth.
More about this job
Responsibilities
The role involves managing business rules and complex reporting workflows to support finance and merchandising decisions. You will also build Tableau dashboards, perform root-cause troubleshooting, and integrate AI tools to automate and modernize data processes.
Requirements
Candidates must hold a bachelor's degree in a quantitative field and possess 2 to 6 years of experience in analytics or business intelligence. Proficiency in SQL, Tableau, and advanced Excel is required, with retail industry experience considered a significant asset.
Skills
- SQL
- Tableau
- Data Analysis
- Financial Acumen
- Python
- Business Intelligence
- Troubleshooting
- AI Fluency
- Microsoft Office
- Power Query
- XLOOKUP
- Test Design
- Reporting
- Process Optimization
- Consultative Partnership
- Data Quality
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Finance & Accounting
- Retail
- Technology
- Consulting
Keywords
- SQL
- Tableau
- Python
- BigQuery
- Alteryx
- Gemini
- Copilot
- NotebookLM
- Power Query
- XLOOKUP
- Retail
- Finance
- Merchandising
- Data Products
- Scorecards
- AI Tools
- Business Analytics
- Statistics
- Economics
- Computer Science
- Engineering
- Test and Learn
- Cost-benefit Analysis
- Automation
- Workflow Modernization
- Data Quality
- Product Ownership
- Financial Performance
- Margin
- Profitability