Job Snapshot
Company: Meta
Role: Data Engineer, Product Analytics (University Grad)
Location: Menlo Park, CA
Work Type: Not Provided
Pay Range: $99,008 – $139,000 / year
🔥 DSFOR Insider Take: Why This Role Matters
This University Grad role at Meta offers an incredible opportunity to impact products used by billions. You’ll gain hands-on experience in **scalable data solutions** and **product development**, working with some of the world’s largest datasets. It’s a prime launching pad for a career in data engineering within a top-tier tech company.
Role Overview & Responsibilities
As a Data Engineer, you’ll collaborate with software engineering, data science, and product management teams to build data solutions that optimize growth and user experience across Meta’s applications.
- Design and build extensive data sets to craft user and business experiences.
- Develop scalable data solutions to optimize growth, strategy, and user experience for billions of users.
- Guide teams by building optimal data artifacts, including datasets and visualizations.
- Refine systems, design logging solutions, and create scalable data models.
- Ensure data security and quality, suggesting architecture and development approaches.
- Use data to shape product development, identify opportunities, and prioritize projects.
- Communicate data-driven stories and insights to influence partners.
Requirements
- Possess strong technical skills and an analytical mindset.
- Demonstrate a focus on efficiency in data management standards.
- Ability to build credibility through structured and clear communication.
- Capacity to act as a trusted strategic partner.
🎯 Application & Resume Tips for Meta
Highlight Analytical Mindset: Showcase projects or experiences where you’ve used an analytical mindset to solve complex problems or design data solutions, as this is a core skill for the role.
Emphasize Scalability: Describe any experience with large datasets or building scalable systems, connecting it to Meta’s vast user base and data challenges.
Storytelling with Data: Provide examples of how you’ve communicated data insights effectively to influence decisions or drive product changes, demonstrating your “data-driven stories” ability.
