Sr. Business Analysis Manager - Technical Lead

T-Mobile•Bellevue, WA

2d•$96,700 - $174,400•Hybrid

About The Position

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.

Requirements

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.
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
4–6 years Experience setting technical standards and mentoring team members in a senior role
Deep technical expertise in modern data infrastructure practices, including pipeline design, orchestration, automation, and reliability.
Strong opinions on data quality, testing, and technical rigor — has built systems that don't need constant babysitting.
Big data and clickstream experience at enterprise scale.
Hands-on Databricks experience, including notebook development, job orchestration, and Unity Catalog.
Strong Python and SQL — comfortable owning end-to-end pipelines independently.
Excellent communication skills — able to explain technical decisions to non-technical stakeholders and influence through fact-based recommendation.
Experience with cloud computing platforms such as Azure, AWS, or GCP.
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Experience with data visualization tools such as Power BI, Tableau, etc.
Adobe Analytics or comparable clickstream tool experience.
Experience with media, marketing, or digital data.
Telecommunications industry experience.

Responsibilities

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.
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.
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.
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.
Partner with peer analytics teams to align on shared conventions and standards, ensuring consistency between macro-level analytics and diagnostic reporting.
Provide guidance and uplift the technical capabilities of the broader team.
Set the technical standard and help less senior team members grow into it.
Serve as the technical lead for major data platform transitions, cloud migrations, and consolidating media reporting infrastructure across teams.
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.