Senior Manager, Data Analytics-CES Data Enablement (Return Business)
Walmart
Data Science
USD 90k-180k / year + Equity
Posted on Apr 28, 2026
Position Summary...
Our Customer Engagement Services (CES) team, formerly the Walmart Care team, is leading big changes to improve both customer experience and business outcomes. We're using advanced technology, AI, and data to turn customer service into a key driver of impact—not just a support function. We’re helping leaders gain powerful customer insights, improve satisfaction, reduce issues, and cut costs—all aligned with Walmart’s Every Day Low Cost (EDLC) approach. As the Data and Analytics team in CES, our mission is to turn customer interactions into actionable insights that shape strategy and deliver measurable results across the business.We are seeking a highly skilled and hands-on Sr. Manager of Data Enablement to lead the development of a robust data foundation for the Returns business within Customer Engagement Services (CES). This role will focus on designing scalable data models, enabling trusted data structures, and accelerating actionable insights that guide business decisions and measure impact.
As a key partner across analytics, product, and data engineering teams, this role will translate complex business needs into structured data solutions—ensuring data is reliable, accessible, and optimized for reporting, analytics, and insight generation. This position plays a critical role in enabling a single source of truth and driving measurable improvements in customer experience, cost reduction, and operational efficiency.
What you'll do...
Data Foundation & Modeling (Returns Focus)- Design and build scalable, standardized data models to support Returns analytics, reporting, and insight generation.
- Establish clean, structured datasets that enable consistent KPI tracking (e.g., returns rate, defect drivers, cost impacts).
- Ensure data structures are extensible to support future business needs and additional use cases.
- Develop and maintain a trusted data foundation that powers dashboards, reporting, and advanced analytics.
- Eliminate data inconsistencies by aligning definitions, metrics, and sources across teams.
- Enable a unified data layer that supports self-service analytics and reduces manual data validation work.
- Work closely with Data Engineering to define data requirements, optimize pipelines, and improve data latency and reliability.
- Collaborate with analytics teams to ensure data models support business questions, root cause analysis, and actionable insights.
- Translate business requirements into scalable data solutions and technical specifications.
- Define and enforce data governance standards, including metric definitions, lineage, and quality controls.
- Ensure Returns data is accurate, consistent, and decision-ready across reporting and analytics use cases.
- Proactively identify and resolve data gaps or inconsistencies.
- Enable analytics that identify key drivers of returns, customer pain points, and operational inefficiencies.
- Support measurement frameworks to evaluate impact of business initiatives (e.g., return reduction, policy changes, self-service improvements).
- Partner with stakeholders to ensure data outputs translate into actionable business decisions.
- Continuously improve data structures, processes, and enablement capabilities to reduce time-to-insight.
- Leverage emerging technologies (e.g., GenAI, automation) to enhance data accessibility and insight generation.
- Identify opportunities to scale data solutions across CES and broader Walmart use cases.
- Bachelor’s degree in Data Analytics, Data Science, Engineering, Statistics, or related field; Master’s preferred.
- 5+ years of experience in data enablement, data modeling, analytics engineering, or related roles
- Strong experience working in highly cross-functional environments
- Experience supporting product, operations, or customer experience domains (Returns experience preferred)
- Deep expertise in data modeling, data structures, and scalable data architecture
- Strong experience with SQL/AI Coding tool and working with large-scale data platforms
- Experience partnering with Data Engineering on pipelines, ETL processes, and data optimization
- Strong understanding of data governance, quality frameworks, and best practices
- Strong business acumen with ability to connect data solutions to measurable outcomes
- Ability to translate complex data concepts into clear, actionable insights
- Excellent stakeholder management and cross-functional collaboration skills
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
For information about benefits and eligibility, see One.Walmart.
The annual salary range for this position is $90,000.00 - $180,000.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
- Stock
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Minimum Qualifications...
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
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.1 year's supervisory experience.
Preferred Qualifications...
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
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), Supervisory experience

















