• Architect complex, high-volume data pipelines for production use. • Design and implement scalable data models serving multiple product and internal teams. • Own data quality frameworks and standards across key data products. • Build reusable patterns for transformations and metrics to drive efficiency. • Define and maintain core business metrics and Key Performance Indicators (KPIs) in partnership with Analytics. • Own the data products used across the company, ensuring reliability and performance. • Set and promote standards for data modeling and pipeline development. • Partner closely with Analytics, Data Science, and Machine Learning teams on requirements to reduce friction and accelerate their work. • Mentor engineers and actively participate in the hiring process.