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Specialist, Intelligence & Analytics

Job in Bellevue, King County, Washington, 98009, USA
Listing for: T-Mobile
Full Time position
Listed on 2026-09-14
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Business Intelligence, Data Engineering, Business Systems & Technology Analysis
Salary/Wage Range or Industry Benchmark: 64600 - 128150 USD Yearly USD 64600.00 128150.00 YEAR
Job Description & How to Apply Below

At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That’s how we’re UNSTOPPABLE for our employees!

This role is responsible for building and maintaining the technical systems that power T-Mobile’s compensation operating model. This role sits at the intersection of applied AI, data engineering, and compensation strategy—designing scalable internal tools that automate complex workflows, centralize compensation data, and replace manual or vendor-dependent processes. The ideal candidate combines hands‑on technical depth with the business fluency to translate compensation logic into auditable, enterprise‑grade systems that serve both day‑to‑day operations and executive decision‑making.

  • Design, build, and continuously improve internal compensation workflow platforms that automate end-to-end processes—including intake, evaluation, benchmarking, approval routing, audit trail documentation, and downstream system integration—reducing reliance on manual effort and third‑party tools.
  • Architect and develop AI‑enabled systems—including natural‑language query interfaces and retrieval‑based applications—that provide on‑demand access to centralized compensation data, replacing static reporting with dynamic, always‑on analytical capability.
  • Engineer and maintain structured data pipelines that unify compensation, labor market, and job architecture data into reliable, governed data assets that support both operational workflows and executive decision‑making.
  • Integrate compensation platforms with enterprise systems and reporting tools to ensure real‑time data visibility, reduce manual reconciliation, and deliver scalable, reproducible insights to compensation and HR stakeholders.
  • Diagnose and resolve technical issues across the compensation systems stack—spanning APIs, data connections, workflow logic, and pricing models—in close collaboration with compensation operations, HR technology, and business stakeholders.
  • Also responsible for other Duties/Projects as assigned by business management as needed.
Education and

Work Experience:
  • Bachelor's Degree plus 2 years of related work experience OR combination of education and experience deemed equivalent Required Acceptable areas of study include HR, Communication, Business, or related field
  • Master's Degree Preferred
  • 2 – 4 years Strong proficiency in Python and SQL; hands‑on experience building applied AI systems including LLM‑based applications, retrieval‑augmented generation (RAG), and agentic workflows. (Preferred)
  • 2 – 4 years Experience designing and building multi‑step workflow applications with complex state management, audit trail logic, SLA tracking, and role‑based access or approval flows. (Preferred)
  • 2 – 4 years Experience integrating enterprise data sources and APIs (e.g., Workday, Power BI, or equivalent HCM/BI platforms); familiarity with compensation, HR, or workforce analytics domains preferred. (Preferred)
Knowledge, Skills and Abilities:
  • Ability to independently own complex, multi-workstream technical projects from design through deployment; diagnose and resolve cross‑system technical issues; translate compensation business logic into precise technical specifications; communicate clearly with both technical and non‑technical stakeholders; strong audit and documentation discipline; thrives in ambiguous, fast‑moving environments. (Required)
  • At least 18 years of age
  • Legally authorized to work in the United States

Total…

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