Architect, build, and maintain data pipelines to ingest, process, and transform logs and signals from various Geo services for scraping detection and analysis.

Implement and manage data quality frameworks, leveraging AI and automation to enhance data ingestion, ensure data integrity, and improve the accuracy of anti-scraping models and analytics.

Develop and maintain curated datasets, reports, queries, and dashboards to support client users in understanding and mitigating scraping threats.

Drive the creation of automated solutions and self-service tools to accelerate data-driven decision-making and improve the efficiency of anti-scraping operations and partner care experiences.

Provide operational support for anti-scraping data systems, including performance monitoring, post-launch issue resolution, proactive planning for dependency changes and system migrations, while defining and driving the long-term technical goal and roadmap for a scalable, resilient, and cost-effective anti-scraping data infrastructure for Google Maps.

Bachelor's degree or equivalent practical experience.

5 years of experience designing, building, and managing production-grade ETL pipelines.

Experience writing readable, structured code (e.g., Python, Java) and applying AI/ML libraries/frameworks (e.g., Tensor Flow, Vertex AI) within data systems.

Experience applying AI/ML techniques to anti-abuse, security, or fraud detection.