Pitney Bowes Inc.

Pitney Bowes Inc.

RevOps Analytics Manager

US CT Shelton · Senior

No sponsorship$100k-$120kDetected 6 days ago
SQLSnowflakeData AnalysisData EngineeringData ScienceStatisticsProject ManagementSalesforceSalesForecastingSAPCadenceLeadershipCommunication

About the role

  • We have amazing people who are the driving force, the inspiration and foundation of our company.
  • Our thriving culture can be broken down into four components: Client.
  • We actively look for prospects who: • Are passionate about client success. • Enjoy collaborating with others. • Strive to exceed expectations. • Move boldly in the quest for superior and best in market solutions.

Nice to have

  • Ensure data accuracy and consistency across systems, sources, and reports.
  • Conduct deep‑dive analyses to identify trends, patterns, and opportunities to improve performance, efficiency, and productivity.
  • Establish a regular cadence of insights delivery to stakeholders and executive leadership.
  • Bachelor's degree in technology or a quantitative field (Analytics, Statistics, Economics, Data Science, Applied Math) or equivalent experience.
  • 4-5 years of experience in data analysis and reporting.
  • At least four years of advanced SQL experience for data extraction, transformation, and modeling.
  • Advanced experience using Snowflake for analytics.
  • Strong foundational knowledge of Salesforce, SAP, and Oracle OLFM.

Compensation

  • The base range for this position is $100,000 - $120,000 per year, with the actual pay dependent on your skills and experience as they relate to the job requirements and the location where you will be performing the job.

Company info

  • At Pitney Bowes, we do the right thing, the right way.
  • As a member of our team, you can too.

Visa & Work Authorization

  • Must be legally authorized to work in the US.
  • Employer will not sponsor position for employment visa status now or in the future (ex.

This listing is sourced directly from Pitney Bowes Inc.'s careers page and normalized into a canonical job model.