Designs and owns large-scale AWS architectures and Databricks lakehouse platforms; leads Terraform, policy-as-code, CI/CD, observability, AIOps, governance, incident escalation, and cross-team initiatives. The role mentors engineers, documents architecture, evaluates emerging technologies, and communicates technical decisions to stakeholders while improving platform reliability, scalability, security, and cost efficiency.

Lead design and implementation of data platform architecture and pipelines (ELT) using Spark/Databricks and AWS. Ensure governance, metric consistency, security, and performance of business-critical datasets. Troubleshoot and optimize data processing, enable analytics access, define table/metric standards, and mentor engineers to deliver reliable data services.

Lead and execute high-impact AI/ML initiatives: prototype and deploy agentic AI, build predictive models and experiments to optimize ad performance and monetization, analyze large datasets, improve pipelines and experimentation frameworks, evangelize modeling best practices, mentor data scientists, and communicate findings to technical and non-technical stakeholders.