Payton Baughman

Owned enterprise data platform strategy and roadmap, defining a hub-and-spoke operating model to accelerate domain execution. Introduced platform telemetry and compute cost transparency, and implemented data lifecycle/compute policies reducing cost per platform user from $1100/mo to $400/mo.

Established platform patterns for emerging AI/ML use cases, including agentic workflows and medallion architecture for unstructured data. Migrated 200+ data products to dbt, improving compute efficiency ~20%, and built cross-platform data interoperability (ADLS ↔ Snowflake) using Delta/Iceberg formats.

Built T-Mobile’s first lakehouse and enabled scalable analytics, improving query performance from ~3 minutes to ~10 seconds while scaling to 17K+ datasets and 75K daily jobs. Defined a data contract framework standardizing 200+ data products with embedded governance and quality controls, increasing platform adoption by 90%+ and onboarding 305 users in 6 months.

Developed enterprise analytics across SAP and PeopleSoft, building OLAP models and standardized analytical frameworks to improve reporting consistency. Improved data accessibility by creating documentation and metadata to streamline self-service analytics adoption.

Delivered workforce planning analytics for staffing, call volume forecasting, and service-level performance across 40+ global call centers. Built automated SQL/Power BI/Alteryx reporting and dashboards to improve operational visibility and decision-making.

Progressed through frontline support and escalation management roles, resolving complex customer issues and improving service outcomes. Owned workforce scheduling and service-level reporting to optimize operational performance and customer experience.

Completed a Data Science Bootcamp program (certification) in 2021.

Completed a Bachelor’s program in Operations Management and Analysis with a focus on Data Science in 2018.