Want to get hired at Meta?
Data Engineer, Product Analytics
Meta
Original Job Summary
About the Role
As a Data Engineer, Product Analytics at Meta, you will shape the future of people-facing and business-facing products across Facebook, Instagram, Messenger, WhatsApp, Reality Labs, and Threads. Your technical skills and analytical mindset are essential in designing and building extensive data sets that support billions of users and hundreds of millions of businesses worldwide.
Responsibilities
- Conceptualize and own the data architecture for large-scale projects.
- Create frameworks to improve logging data and manage production issues.
- Collaborate with engineers, product managers, and data scientists to design meaningful data visualizations.
- Define and manage Service Level Agreements for data sets.
- Design, build, and launch sophisticated data models and visualizations.
- Solve challenging data integration problems using optimal ETL patterns.
- Optimize pipelines, dashboards, and systems for efficient data artifact development.
- Influence product and cross-functional teams to drive impact through data insights.
- Mentor team members through actionable feedback.
Minimum Qualifications
Bachelor's degree in Computer Science, Computer Engineering, or related field; 7+ years working with data including SQL, ETL, data modeling, and programming (Python, C++, C#, Scala, etc.).
Preferred Qualifications
Master's or Ph.D. in a STEM field.
About Meta
Meta builds technologies that help people connect, build communities, and grow businesses. From social networking to immersive AR/VR experiences, Meta is at the forefront of innovative digital transformation.
Key skills/competency
- Data Engineering
- SQL
- ETL
- Data Modeling
- Data Architecture
- Python
- Visualization
- Scalability
- Analytics
- Mentorship
How to Get Hired at Meta
🎯 Tips for Getting Hired
- Customize Your Resume: Tailor your resume to highlight data engineering skills.
- Research Meta Culture: Understand Meta's mission and recent projects.
- Showcase Relevant Experience: Emphasize SQL, ETL, and data modeling expertise.
- Prepare for Technical Interviews: Brush up on coding and algorithm challenges.
- Network Strategically: Connect with current Meta data professionals on LinkedIn.