• Own mission-critical pipeline reliability: Take end-to-end ownership of our production data pipelines processing billions of messages weekly, ensuring 99.9% uptime for revenue-critical pipelines that directly enable sales and customer-facing AI products • Build self-healing pipelines: Design and implement automated monitoring, testing, and recovery systems for data pipelines that eliminate manual intervention and reduce MTTR from hours to minutes • Accelerate development velocity: Deploy CI/CD pipelines and self-service platforms that reduce deployment time from 3-5 days to under 2 hours, enabling Data Scientists to safely deploy models without engineering bottlenecks • Architect for scale: Optimize data pipelines handling exponential annual growth, implementing cost-effective solutions that support regional expansion and compliance requirements (GDPR, FedRAMP, SOC2) • Bridge technical and business domains: Partner with Sales, Finance, and Product teams to ensure data infrastructure aligns with business needs, making critical trade-off decisions when pipelines impact revenue • Establish data engineering excellence: Define best practices for dbt, Airflow, Spark usage, PII anonymization, and cross-divisional data sharing while mentoring embedded Data Guild team members on these. • Enable AI and accessible data consumption: Design and maintain an accessible semantic layer that provides consistent, trustworthy definitions and abstractions, making it easy for stakeholders to consume data and incorporate AI-driven insights into their workflows.