Senior Data Analyst

Walmart•Bentonville, AR

7d•Onsite

About The Position

The Senior Data Analyst identifies suitable, fit-for-purpose data sources, understands business data requirements and service-level agreements, and performs initial quality checks on extracted data. The role applies data strategy principles to routine business problems, including data management, quality standards, governance, accessibility, storage, scalability, and methods for unlocking the value of data assets. The analyst connects business needs to data-driven solutions by understanding relevant business practices, metrics, and context. The role provides recommendations to stakeholders on complex business issues, develops business cases with projected return on investment or cost savings, translates requirements into projects and tasks aligned with business strategy, and identifies relevant insights. The position formulates business problems as data-related or mathematical solutions, selects suitable methods and tools, and communicates how those methods address business needs. It also creates visual representations of data and model outcomes, designs visualizations for multiple datasets, collaborates with user experience designers and user interface engineers as needed, and presents findings to business audiences using clear, stakeholder-appropriate communication. The position is located at 811 Excellence Dr, Bentonville, AR 72716. Pay is $96,616.00–$155,000.00 per year, with additional annual or quarterly performance incentives.

Requirements

Master’s degree or equivalent in Information Technology and Management, Engineering (any), or a related field; or a bachelor’s degree or equivalent in one of these fields and 2 years of experience in data analytics or a related field.
Experience cleaning data and performing deep-dive analytics to tell a story using Google Cloud Platform.
Experience creating dashboards for reporting and visualization using Tableau.
Experience performing regression and creating bar plots using statistical analysis with R.
Experience organizing projects using waterfall or agile methodologies.
Experience using SQL to extract data from databases and analyze data using SSMS.
Experience using relational databases to interact with data, including creating, updating, traversing, and merging.
Experience creating schedulers to automate tasks, including sending emails and project tracking, using Microsoft Power Automate.
Experience cleaning data and exporting it into SSMS using Python.
Experience reporting and formatting data, implementing calculated fields, and performing VLOOKUP and macros using Excel.
Experience creating ETL processes to automate data fetching, transformation, and conversion into usable tables.

Responsibilities

Identify business data requirements, data categories and locations, relevant database technologies, existing business systems, processes, and measures of success.
Help determine the priority order of requirements and service-level agreements, identify appropriate data sources, and perform initial data quality checks on extracted data.
Apply data strategy principles to routine business problems, including data management, data quality standards, governance, accessibility, storage, scalability, and data asset value.
Provide recommendations to business stakeholders to address complex business issues.
Develop business cases for projects with projected return on investment or cost savings.
Translate business requirements into projects, activities, and tasks aligned with overall business strategy, and develop domain-specific artifacts.
Connect business needs with tangible solutions and results, and identify relevant business insights.
Translate or co-own business problems within the discipline as data-related or mathematical solutions; identify appropriate methods and tools and explain their application through use cases.
Create appropriate graphical representations of data and model outcomes and design data representations for multiple datasets.
Work with user experience designers and user interface engineers as required to build front-end applications.
Present findings to teams and business audiences using appropriate data visualization frameworks and clear messaging, tailoring communication to stakeholders.