Director, Data Engineering

Job Description

About the Role

Do you like working with big data? Do you want to use data to help drive the direction of products that impact the lives of over one billion people every day? If yes, we want to talk to you. We're looking for a leader in our Data Engineering team to work closely with Product Managers, Data Scientists, Software Engineers and ML Engineers to support our world class AI Infra roadmap by building the data architecture that informs decisions and drives insight. In this role, you'll see a direct link between your work, company growth, and user experiences. You'll work with some of the brightest minds in the industry, work with one of the richest data sets in the world, use cutting edge technology, and you'll see your efforts affect products and people on a regular basis.

Key Responsibilities

Proactively formulate and implement the vision for the foundation for data and analytics to support the Infrastructure org and its goals.
Drive technical and process innovation to increase the maturity and capability of Infrastructure data engineering team and practices.
Establish the processes needed to achieve operational excellence in data fidelity, data privacy, system reliability, and enabling rapid experimentation and data-informed decisions.
Manage and grow a high-quality data engineering team.
Partner with cross-functional teams of Data Scientists, Software Engineers, Product Managers, Researchers, and other partner groups to understand their data needs and deliver on them.
Drive the design, building, and launching of new data models and data pipelines in production.
Define and manage SLAs for all data sets and processes running in production.
Drive data quality across the product vertical and related business areas.
Manage the delivery of high-impact dashboards, data sets, and data visualizations.
Contribute to improving data engineering competency across Facebook.

Requirements

12+ years of experience in Analytics, BI and Data Warehousing.
Experience scaling and managing 20+ person teams and in managing managers.
Experience leading in a highly cross-functional environment, likely collaborating closely with Engineering, Product Management, and/or Data Science.
Communication and leadership experience, with experience initiating and driving large scale strategic initiatives.
Data architecture experience.
Experience in SQL or similar languages.
Development experience in at least one object-oriented language (Python, Java, etc.).
Solid understanding of how experimentation (A/B testing) works.
BA/BS in Computer Science, Math, Physics, or other technical fields.
Experience with ML development lifecycle.
Experience working on large scale infrastructure.
Experience with automating data auditing through comprehensive lineage tools.
Experience with large volume data sets, Hive/Presto, and data visualization tools.