Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.
Responsibilities
Design and develop creative and innovative solutions to transform data coming from diverse domains and components operating in facebook.com, such as advertisements and pages, as well as other custom software systems and databases. Facilitate visibility and consumption of the domains and components via appropriate interfaces. Design, architect, and develop data solutions that help product and business teams make data driven decisions. Lead data solution design efforts from beginning to end, as well as processes for the development and implementation of data integration for external insights, and will perform data engineering efforts for the Data Warehouse and Operational Data Store. Provide insights that influence overall strategy and plan for the framework and construction of a scalable data solution and data warehouse environment. Leverage homegrown Extract, Transform, Load (ETL) framework as well as the off-the-shelf tools, as appropriate. Collaborate with data infrastructure and engineering teams to build and extend cross-platform ETL and reports generation frameworks. They will provide consultation to business partners, including analysts, managers, end users and developers to clarify work objectives, determine project scope, obtain consensus, identify problems and recommend solutions. Will also support end users on ad hoc data usage and serve as subject matter experts on functional matters.
Qualifications
Bachelor's degree (or foreign degree equivalent) in Computer Science, Engineering, Data Science, Information Systems, Mathematics, Statistics, Data Analytics, Applied Sciences, or a related field Requires completion of a university-level course, research project, internship, or thesis in the following: Features, design, and use-case scenarios across a big data ecosystem Custom ETL design, implementation, and maintenance Object-oriented programming languages Schema design and dimensional data modeling Writing SQL statements Analyzing data to identify deliverables, gaps, and inconsistencies Managing and communicating data warehouse plans to internal clients MapReduce or MPP system and Python