Data Engineering Leader, Analytics

Meta

Menlo Park (CA)

On-site

USD 210,000 - 320,000

Full time

14 days+

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Job summary

Meta in Menlo Park is seeking a senior leader to own BI and data warehousing strategy and delivery. You will lead cross-functional teams of data scientists, engineers, and product managers to design, implement, and scale data models, pipelines, and dashboards that power Meta's ads infrastructure and monetization decisions.

You will drive operational excellence, governance, and AI-enabled improvements while managing a growing team and aligning with product goals across platforms.

Qualifications

  • 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 and staying current with AI technologies.
  • Experience with data sets, Hadoop, and data visualization tools.
  • Advanced degree.
  • Experience adhering to and implementing responsible, ethical AI practices (risk assessment, bias mitigation, quality and accuracy reviews).
  • Demonstrated ability to integrate AI tools to optimize workflows and drive impact.
  • Experience in a consumer web or mobile company.

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 processes needed to achieve operational excellence in project management and system reliability.
  • Proactively drive the vision for BI and Data Warehousing across a product vertical and execute on a plan.
  • Build a high-quality BI and Data Warehousing team and design the team to scale.
  • Manage data warehouse plans across a product vertical.
  • Drive 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 SLAs for all data sets and processes running in production.

Skills

BI & Data Warehousing
Leadership
Cross-functional collaboration
Project management
Data architecture
SQL proficiency
Python/Java
AI skills development
Data visualization
Hadoop experience
Responsible AI practices
Consumer web/mobile experience

Education

Bachelor's degree in Computer Science or related field
Advanced degree

Tools

Hadoop
Data visualization tools

Job description

About

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
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