Sr. Data Analyst

About the role

This role is based at 625 Westport Parkway, Grapevine, TX 76051, and the working hours are Monday to Friday, 9:00 am to 5:00 pm. The salary for this position is $146,515.00 per year.

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, as well as obtaining input from managers to adjust forecasts as necessary.
• Forecasting inbound, outbound, and inventory volumes weekly.
• Compiling monthly spend for the ROC and allocating said spend to send to Director of Finance and Financial Analyst.
• Communicating these numbers to managers, and answering any questions or concerns as needed.
• 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 to deploy on the floor.
• Updating WBR and Exec WBR slides weekly and making adjustments as necessary.
• Creating, analyzing, and maintaining Power BI reports with the use of SQL and Python.
• Using knowledge obtained from creating these reports to explain concepts and outliers to managers and supervisors.
• Maintaining knowledge of data sources pertinent to the ROC and using said knowledge to pull data quickly and efficiently when requested.
• Communicating with colleagues inside and outside of the ROC to answer questions posed by managers.
• Available on short notice to provide key metrics to business leaders in the pre-owned business.
• Coordinate 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.
• 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.

Qualifications

A 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 in which the required experience was gained. Alternatively, a 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 in which the required experience was gained.

Applicants must have demonstrated experience with: Proficient database and querying skills including SQL; Data platforms and applications such as BigQuery, Power BI and similar platforms; 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; and Python.

Skills

• Proficient database and querying skills including SQL.
• Data platforms and applications such as BigQuery, Power BI and similar platforms.
• 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.
• Python.