Build and maintain scalable data pipeline architecture, process complex datasets, improve data delivery and infrastructure, and support data initiatives across engineering, product, business intelligence, and data science teams. Develop extraction, transformation, and loading infrastructure using Spark, EMR, Kafka, and other big data technologies while optimizing production-scale data and machine learning pipelines.

Lead and scale application security by embedding automated SAST/DAST/SCA testing into CI/CD, administering GHAS, performing pentests and threat modeling, coordinating vulnerability management, securing cloud-native workloads (AWS), and training engineers on secure coding and incident handling to improve overall security posture.

Serve as the technical, client-facing lead for ad campaign activation and troubleshooting. Set up, QA, monitor performance, resolve discrepancies, partner with product/engineering, build dashboards, and provide consultative support across DSPs to optimize campaigns.