Finance Manager- Marketing

T-Mobile T-Mobile · Telecom · Bellevue, WA +2

Finance Manager role supporting Marketing and T-Studio production partners. Focuses on connecting campaign-level production tracking with GL vendor spend, developing processes for cost tracking, and providing reporting, insights, and forecasting for decision-making. Manages budgeting, forecasting, and long-range planning for Marketing and production-related spend.

What you'd actually do

  1. Connect T-Studio’s campaign-level production tracking to GL vendor-level spend to create a unified, accurate view of costs.
  2. Develop repeatable processes to reconcile and align data across systems, enabling reliable reporting and forecasting.
  3. Manage budgeting, forecasting, and long-range planning for Marketing and production-related spend, including fixed, variable, and talent costs.
  4. Support month-end and quarter-end close activities, including variance analysis, accruals, and reconciliation of production-related spend.
  5. Provide insights on spend drivers, campaign economics, and resource allocation to guide Marketing and T-Studio leadership.

Skills

Required

  • Bachelor’s degree in Finance, Accounting, Economics, or related field
  • 5+ years of experience in financial planning & analysis (FP&A)
  • Advanced Excel and financial modeling skills
  • Experience with ERP and planning tools (e.g., SAP, Oracle)
  • Experience working with large, messy data sets and building automated solutions to clean, match, and reconcile data
  • Excellent communication and business partnering skills
  • Ability to work independently in a fast-paced, dynamic environment
  • Experience in developing and presenting business cases
  • Strong quantitative skills
  • Knowledge of Data-base environments (MS SQL Server)
  • Knowledge of Power Bi
  • Excellent analytical and problem-solving skills

Nice to have

  • MBA or CPA a plus

What the JD emphasized

  • building scalable, accurate way to track fixed, variable, and talent-related costs
  • spend visibility
  • operational clarity
  • accountable decision-making
  • large, messy data sets
  • building automated solutions to clean, match, and reconcile data
  • building structure where none exists
  • Holds themselves and others accountable
  • digging into the details
  • data design
  • reporting automation
  • system integration