Senior, Data Analyst - Fashion Network

Walmart Walmart · Retail · Bentonville, AR

Senior Data Analyst role focused on leveraging data analytics, reporting, and visualization to support business objectives within the Fashion Distribution Network. Responsibilities include developing and optimizing reports (Power BI, Tableau), querying data, ensuring data quality, performing exploratory data analysis, and communicating insights to stakeholders. The role also involves mentoring junior associates and ensuring compliance with company policies.

What you'd actually do

  1. Develop, maintain, and optimize Power BI and Tableau reports.
  2. Write and execute data queries, ensuring data quality and accuracy.
  3. Navigate and understand existing data sources and architecture to support business needs.
  4. Perform initial data quality checks and support ongoing data quality management.
  5. Apply statistical techniques and exploratory data analysis to identify trends, patterns, and insights.

Skills

Required

  • Bachelor's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Arts, Finance or related field and 2 years' experience in data analysis, data science, statistics, or related field OR Master's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field OR 4 years' experience in data analysis, data science, statistics, or related field.
  • Develop, maintain, and optimize Power BI and Tableau reports.
  • Write and execute data queries, ensuring data quality and accuracy.
  • Navigate and understand existing data sources and architecture to support business needs.
  • Perform initial data quality checks and support ongoing data quality management.
  • Apply statistical techniques and exploratory data analysis to identify trends, patterns, and insights.
  • Collaborate with business stakeholders to translate requirements into actionable data projects.
  • Present data findings using advanced visualization techniques and communicate insights to technical and non-technical audiences.
  • Mentor junior associates on data visualization and analytics best practices.
  • Ensure compliance with company policies, data governance, and regulatory requirements.
  • Drive analysis and insights that simplify work in the Fashion Distribution Network and improve throughput, service, and cost.
  • Communicate complex findings in clear, decision-ready stories for field leaders, ops partners, and leadership.
  • Bring creative thinking to ambiguous problems - generate options, test ideas quickly, and iterate based on results.
  • Operate with high ownership and self-direction - prioritize effectively, manage deadlines, and unblock yourself/others.
  • Build strong working relationships with site partners; listen, synthesize feedback, and incorporate frontline realities.
  • Maintain a high bar for quality: accuracy, clarity, documentation, and a bias toward action over analysis-only deliverables.

Nice to have

  • Proven experience in reporting development using Power BI and Tableau.
  • Advanced skills in Python and data analytics.
  • Strong understanding of database technologies (SQL, NoSQL) and distributed datastores.
  • Experience with data quality management, data modeling, and data integration.
  • Ability to translate business problems into data-driven solutions.
  • Excellent communication and stakeholder management skills.
  • Interest or experience in web development is a plus.
  • Knowledge of the fashion or distribution center environment is preferred.
  • 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).

What the JD emphasized

  • Ensure compliance with company policies, data governance, and regulatory requirements.
  • Maintain a high bar for quality: accuracy, clarity, documentation, and a bias toward action over analysis-only deliverables.