Data Engineering Leader, Analytics

Ads Infra is a critical part of Meta's business, responsible for building and maintaining the Serving and Data infrastructure that powers the company's advertising products. The mission is to ensure the reliability, scalability, and efficiency of the ads platform, which includes everything from data storage and processing to ML, inference, and algorithm development. Ads Ranking & AI Infrastructure org is responsible for delivering ads across all our placements (Facebook, Instagram, Messenger, WhatsApp, etc.). The team has consistently contributed the major part of overall Meta’s revenue growth over the years. At the same time, we have been the trailblazer for Meta’s most complex recommender system, e.g., delivering the first NN recommender model and landing the first large GPU powered recommender model. Together with the Infra + Ranking DS team, the Ads Online Infra DE team supports the ML Infra team with analytics solutions that ensure data and serving infrastructure remain highly reliable and any negatively impacting issues that arise are quickly identified and mitigated. We are responsible for the entire monetization's capacity management and reliability effort. The Ads Online Infra team is directly involved in Monetization, AI, and Capacity, key company priorities. The key product area we support is Monetization Capacity. End-to-end Monetization infrastructure capacity usage, supply and demand, and efficiency footprint across CPU, GPU, and Shared Platforms.

Responsibilities

• Manage the delivery of high impact dashboards and data visualizations
• Build cross-functional relationships with Data Scientists, Product Managers and Software Engineers to understand data needs and deliver on those needs
• Define the processes needed to achieve operational excellence in all areas, including project management and system reliability
• Proactively drive the vision for BI and Data Warehousing across a product vertical, and define and execute on a plan to achieve that vision
• Build a high-quality BI and Data Warehousing team and design the team to scale
• Manage data warehouse plans across a product vertical
• Drive the design, building, and launching of new data models and data pipelines in production
• Drive data quality across the product vertical and related business areas
• Define and manage SLA’s for all data sets and processes running in production

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 9+ years of experience in BI and Data Warehousing
• Experience scaling and managing 10+ person teams
• Experience managing managers
• Experience leading cross-functional initiatives and communicating technical strategy to engineering and business stakeholders
• Project management experience
• Data architecture experience
• Experience in SQL or similar languages
• Development experience in at least one object-oriented language (Python, Java, etc.) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience with data sets, Hadoop, and data visualization tools
• Advanced degree
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience in a consumer web or mobile company