Data Center Services Analyst

Switch•Las Vegas, NV

8d•Remote

About The Position

The Data Center Services Analyst turns complex revenue data into trusted reporting and practical insights. You will own reporting for pipeline, bookings, revenue, forecasts, and key go-to-market measures. You will improve data quality and transformation processes across Salesforce and related systems. This is an individual contributor role with independent responsibility for complex analysis and recurring leadership updates.

Requirements

Four or more years of experience in Revenue Operations, Sales Operations, business intelligence, data analytics, business operations, or a related analytical role.
Hands-on experience with Salesforce data, business processes, and downstream reporting.
Advanced SQL skills and experience working with relational data and complex datasets.
Experience building and maintaining Tableau dashboards for business users.
Experience using Python and Power Query for analysis, transformation, automation, or data quality work.
Practical knowledge of ETL and ELT processes, data pipelines, integrations, and data modeling.
Experience supporting pipeline, forecast, bookings, revenue, or operational planning.
Experience creating consistent data definitions, documentation, and validation standards.
Ability to explain technical findings to nontechnical audiences.

Nice To Haves

Experience in B2B technology, data centers, infrastructure, SaaS, or another complex technology environment.

Responsibilities

Build and maintain Tableau dashboards and revenue reports for pipeline, bookings, revenue, forecasts, and key go-to-market metrics.
Own recurring Revenue Operations updates and explain performance, trends, risks, and opportunities to leaders.
Use SQL, Python, and Power Query to clean, transform, validate, and automate revenue data.
Build and maintain ETL and ELT processes that support reliable reporting datasets.
Combine Salesforce and downstream system data into documented, reusable datasets.
Maintain shared definitions, validation rules, and documentation for revenue data.
Trace data issues from source systems through final reports and coordinate practical fixes.
Improve data capture, integrations, and reporting processes to reduce manual work.
Translate business questions from Sales, Marketing, Finance, Operations, IT, and Data into clear analysis.