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.

DATA ENGINEER Responsibilities

• Coordinate and execute data warehouse plans for a product or a group of products to solve well-scoped problems.


• Identify the data needed for a business problem and implement logging required to ensure availability of data, while working with data infrastructure to triage issues and resolve.


• Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights visually in a meaningful way.


• Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership.


• Design, build and launch new data models and visualizations in production, leveraging common development toolkits.


• Independently design, build and launch new data extraction, transformation and loading processes in production, mentoring others around efficient queries.


• Support existing processes running in production and implement optimized solutions with limited guidance.


• Define and manage SLA for data sets in allocated areas of ownership.


• Telecommuting is permitted from anywhere in the United States.

Minimum Qualifications

• Requires a Master's degree in Computer Science, Engineering, Information Systems, Data Science, Analytics, Statistics, Mathematics, or a related field and 24 months of work experience in the job offered or in a related occupation. Foreign degree equivalent accepted. Experience must include 24 months involving the following:


• 1. Data ETL (Extract, Transform, Load) design, implementation, and maintenance on a large scale


• 2. Programming in Python


• 3. Programming in Java


• 4. Writing SQL statements


• 5. Analyzing large volumes of data to provide data driven insights, gaps, and inconsistencies


• 6. Data warehousing architecture and plans


• 7. Dimensional data modeling


• 8. Schema Design


• 9. Map Reduce


• 10. MPP system


• 11. Hadoop and


• 12. Hive.