Data Engineer

Meta•Menlo Park, CA

15d•$194,269 - $199,650

About The Position

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.

Requirements

Requires a Bachelor's degree (or foreign equivalent) in Computer Science, Engineering, Mathematics, or a related field and 6 months of experience in the job offered or in a related occupation
Requires 6 months of experience involving the following:
Data warehouse management
Data modeling
Data visualization
ETL data pipeline and
Python programming

Responsibilities

Design, model, or implement data warehousing activities in order to contribute to the design and development of Meta products.
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 creating 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.
Work on problems of moderate scope where analysis of situations or data requires a review of a variety of factors.
Exercise judgment within defined procedures and practices to determine appropriate action.