Data Engineer, Anti Scraping, Third Party Data Operations

Data Engineer, Anti Scraping, Third Party Data Operations

About the job

In this role, you will support the GASP team which builds technology to protect Geo assets at scale. As a Data Engineer, you will build and manage data pipelines to ensure data sources can be consumed by the Geo Anti-Scraping Program (GASP) for abuse and scraping detection, monitoring and measurement.

Minimum qualifications:

• 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., TensorFlow, Vertex AI) within data systems.
• Experience applying AI/ML techniques to anti-abuse, security, or fraud detection.

Preferred qualifications:

• Experience with AI to drive automation for data pipelines and data quality.
• Experience with data logging, monitoring, and analysis tools.
• Familiarity with distributed systems.
• Understanding of bot detection techniques and adversarial machine learning.
• Ability to manage project timelines and deliverables effectively.
• Excellent stakeholder engagement skills, with experience working with both internal teams and external vendors.

Responsibilities

• 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.