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# Data Analyst / Business Intelligence Analyst (Data Center Operations)

- **Company:** Experis
- **Location:** Redmond, WA, United States
- **Experience:** Experienced
- **Salary:** $143,520.0 - $149,760.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Computer Engineering, Data Centers, Information Engineering, Power BI, Tableau (Software), Software Troubleshooting, Information Technology, Data Analytics
- **Published:** October 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=76481ccc7ed285f5

## About the Role

Top 3 Must-Have HARD Skills & years of experience for each:

 * Conducting data quality verification to ensure accuracy, completeness and consistency across multiple sources, especially for data center (or its equivalent) critical infrastructure health and performance data. (4+ yrs)
 * Performing data analysis to identify trends, anomalies, gaps, and performance opportunities. (4+ yrs)
 * Developing intuitive dashboards and reports that provide clear visibility into metrics, operational health, and program outcomes. (3+ yrs), * Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.
 * 5-7 years of applicable experience in data engineering or related disciplines.
 * Experience designing and implementing data quality validation, verification, and monitoring processes.
 * Strong troubleshooting, problem-solving, analytical thinking, and investigative skills.
 * Experience developing dashboards and visualizations using business intelligence tools such as Power BI, Tableau, or similar platforms.

## Description

* Partner with engineering, operations, and leadership teams to understand objectives, define data requirements, and develop reporting and analytics solutions that drive informed decision-making.
 * Analyze large and complex datasets to identify trends, anomalies, gaps, risks, and opportunities for operational improvement.
 * Perform data quality assessments, validation, and verification activities to ensure data accuracy, completeness, and integrity across multiple sources and systems.
 * Design, implement, automate, and maintain scalable data collection, transformation, and validation processes that reduce manual effort and improve reliability.
 * Develop and maintain dashboards, scorecards, KPI reporting, and self-service analytics solutions that provide visibility into operational performance, telemetry health, program status, and business outcomes.