Sr. Data Analyst

GameStop•Grapevine, TX

2d•Onsite

About The Position

GameStop, Inc. is seeking a Sr. Data Analyst to join their team. This role involves forecasting various business metrics, reporting on financial data, analyzing trends, and maintaining databases. The analyst will create, analyze, and maintain Power BI reports using SQL and Python, and communicate findings to stakeholders at all levels of the organization. The position requires a strong understanding of data sources, the ability to perform ad hoc analysis, and collaboration with various departments including finance, operations, engineering, and C-suite executives. The role also involves analyzing manufacturing execution system (MES) data, developing dashboards for key performance indicators, optimizing SQL queries, and ensuring data accuracy and governance.

Requirements

Bachelor’s degree in Computer Science, Accounting, Finance, Statistics, Mathematics, Business Administration, or a related field of study AND Five (5) years of experience in the job offered or related occupation.
Proficient database and querying skills including SQL.
Experience with data platforms and applications such as BigQuery, Power BI and similar platforms.
Experience creating data visualizations (using Power BI or similar tools) that convey key metrics in an easy-to-understand format for non-technical business decision-makers.
Experience with Python.

Nice To Haves

Master’s degree in Computer Science, Accounting, Finance, Statistics, Mathematics, Business Administration, or a related field of study AND Three (3) years of experience in the job offered or related occupation.

Responsibilities

Forecasting labor, parts/supplies, overhead, and volume month-to-month and yearly.
Reporting forecasted spend, volume, and rates to Director of Finance and Financial Analyst.
Comparing forecast to actuals and historical data, and adjusting forecasts as necessary.
Forecasting inbound, outbound, and inventory volumes weekly.
Compiling monthly spend for the ROC and allocating said spend.
Communicating numbers to managers and answering questions.
Comparing actuals to forecasts to find what contributed to any major differences.
Updating SFC database per supervisor request and per the request of the SFC team.
Working with the SFC team to ensure integrity of the data being obtained and updated.
Moving database information from QA to Prod after testing.
Updating WBR and Exec WBR slides weekly, making adjustments as necessary.
Creating, analyzing and maintaining Power BI reports with the use of SQL (GBQ, PostgreSQL, Azure) and Python.
Explaining concepts and outliers to managers and supervisors using knowledge from report creation.
Maintaining knowledge of data sources pertinent to the ROC and pulling data quickly and efficiently.
Communicating with colleagues to answer questions posed by managers.
Working with ERP Commerce and Operations Director to understand the link between SAP and WM and contributors to Shrink and OOS.
Working with Principal Data Engineer when inventory transactions were not being communicated from WM to GBQ.
Performing ad hoc data reporting/analysis using Excel, PBI, SQL.
Providing key metrics to business leaders in the pre-owned business on short notice.
Coordinating with partners from the C suite level to the operations floor.
Analyzing manufacturing execution system (MES) data related to diagnostics, repairs, cleaning, and quality control to identify operational trends and process bottlenecks.
Developing and maintaining dashboards to monitor key performance indicators (KPIs) such as turnaround time, defect rates, yield, and units per labor hour (CPU).
Providing data-driven insights to support inventory management and supply chain performance.
Designing and optimizing SQL queries to improve data retrieval efficiency for reporting needs.
Maintaining Power BI dashboards for ROC (Return on Capital) reporting.
Collaborating with engineering teams to identify inefficiencies and streamline operational processes.
Conducting root cause analysis to resolve quality issues and support improvements in supplier and vendor performance.
Applying statistical methods and predictive modeling techniques to forecast product demand, optimize inventory levels, and improve production scheduling.
Analyzing return data to support product design enhancements and quality initiatives.
Ensuring data accuracy, completeness, and consistency by implementing and enforcing data quality standards.
Developing automated ETL pipelines into Google BigQuery (GBQ) to support scalable reporting and analytics.
Integrating data from multiple sources to enable centralized analysis.
Implementing data governance best practices and ensuring compliance with data security protocols.
Partnering with manufacturing, electrical, design, and finance teams to deliver actionable insights.
Preparing and presenting analytical findings to business stakeholders.