Product Analytics Data Engineer — Scalable Data & Insights

Meta; Redmond (WA); On-site; USD 114,000 - 173,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta is seeking a Data Engineer to shape the data behind our family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). You will design and build scalable data solutions that serve billions of users and hundreds of millions of businesses, collaborating with software engineers, data scientists, and product managers.

You will manage data warehouse plans, identify data needs, implement logging, and build data models and ETL pipelines in production while upholding

Qualifications

• 2+ years of experience with data in roles like data analyst, data scientist or data engineer.
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field or equivalent practical experience.
• 2+ years of experience with SQL, ETL, data modeling, and at least one programming language.

Responsibilities

• Manage and execute data warehouse plans for a product or group of products to solve well-scoped problems.
• Identify data needed for business problems and implement logging to ensure data availability.
• Collaborate with engineers, product managers and data scientists to understand data needs and present insights.
• Design, build and launch new data models and visualizations in production.
• Independently design, build and launch new data extraction, transformation and loading processes in production.

Skills

SQL

ETL

Data modeling

Python

Data analysis

Education

Bachelor's degree in Computer Science/Engineering or related field

Job description

Meta is seeking a Data Engineer to shape the data behind our family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). You will design and build scalable data solutions that serve billions of users and hundreds of millions of businesses, collaborating with software engineers, data scientists, and product managers.

You will manage data warehouse plans, identify data needs, implement logging, and build data models and ETL pipelines in production while upholding