Sr. Business Analysis Manager - Technical Lead
T-Mobile USA, Inc.About the role
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 position must be located in Bellevue, WA. This is not a remote role - this is a hybrid schedule requiring at least 3 days a week in office.Media Data and Insights (MDI) is T-Mobile's data and AI team for paid media and search — turning massive amounts of data into reliable, AI-augmented insights that drive decisions across the media organization. We own the full data lifecycle from gold-layer transformation through executive-ready reporting, partnering across Media Analytics, Media Enablement, and Engineering to deliver one consistent story of what's working, what isn't, and why.
As the Sr. Business Analysis Manager, Technical Lead, you will be the senior technical partner who makes MDI's data production-ready and trustworthy. You will own the architecture, automation, and technical rigor that ensures our data is reliable, fully automated, and powering the BI and insights the business depends on every week.
In this role, you'll set the technical standards that move the team from manual maintenance to scalable, automated infrastructure — freeing us to deliver higher-value insights faster. You'll partner with peers across Media Analytics, Media Enablement, and Engineering as we deliver major 2026 initiatives across executive reporting, cross-channel media and web behavior insights, and a major clickstream data platform transition.
Key Responsibilities
Technical Architecture and Standards
Own the gold layer architecture across all paid media and search performance data. Set design standards, naming conventions, and patterns that scale across the team and align with peer teams. Define how the team builds, validates, and ships data products.
Production-Ready Data Infrastructure
Build and maintain reliable, automated pipelines in Databricks that don't require constant manual intervention. Establish monitoring, alerting, and SLAs that make our data the source of truth leadership depends on.
Clickstream Data Validation & Partnership
Partner closely with Engineering on enterprise clickstream tables — pageview, visit, and user-level — defining MDI's requirements, validating outputs, and ensuring data quality so the team can analyze web behavior and media impact at scale.
Data Quality Framework
Establish testing, validation, and anomaly detection standards so our data is trusted across the organization. Lead QA against ingestion pipelines, data sources, and platform UIs.
Cross-Team Alignment
Partner with peer analytics teams to align on shared conventions and standards, ensuring consistency between macro-level analytics and diagnostic reporting.
Technical Mentorship
Provide guidance and uplift the technical capabilities of the broader team. Set the technical standard and help less senior team members grow into it.
Major Initiative Leadership
Serve as the technical lead for major data platform transitions, cloud migrations, and consolidating media reporting infrastructure across teams.
Executive Communication
Construct executive-level summaries of technical strategy and present complex architectural decisions in clear, concise terms to non-technical stakeholders. Possess the ability to influence leadership through fact-based recommendations.
Education
Bachelor's degree plus plus 7 years of related work experience OR Advanced degree with 5 years of related experience is required. Acceptable areas of study include Data analysis, data science, decision science, similar quantitative fields or equivalent practical experience.
Work Experience Required
- 7-10 years Building and maintaining production data pipelines and gold/semantic layers in modern cloud data environments
- 7-10 years Hands-on experience with Python and SQL for data pipeline and transformation work
- 7-10 years Working with big data and clickstream data at enterprise scale
- 4–6 years Experience with Databricks, dbt, or equivalent modern transformation and orchestration tooling
- 4–6 years Designing data quality, testing, and validation frameworks<
Apply for this role
Generate a tailored application kit with a matched cover letter, interview prep, and CV highlights — in under 60 seconds.
Apply Now →Generate Application KitFree account required — sign up in 30s