Meta
Data Engineer, Product Analytics

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About the Role
As a Data Engineer at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). Your technical skills and analytical mindset will be utilized designing and building large-scale, complex data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.
In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community. You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining Meta, you will become part of a data engineering community dedicated to skill development and career growth in data engineering and beyond.
Data Engineering
- You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions.
- You will refine our systems, design logging solutions, and create scalable data models.
- Ensuring data security and quality, and with a focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Product Leadership
- You will use data to shape product development, identify new opportunities, and tackle upcoming challenges.
- You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.
Communication and Influence
- You won't simply present data, but tell data-driven stories.
- You will convince and influence your partners using clear insights and recommendations.
- You will build credibility through structure and clarity, and be a trusted strategic partner.
Responsibilities
- Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
- Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
- Define and manage Service Level Agreements for all data sets in allocated areas of ownership
- Solve challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
- Improve logging
- Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
- Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
- Influence product and cross-functional teams to identify data opportunities to drive impact


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Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent
- 2+ years of experience where the primary responsibility involves working with data. This could include roles such as data analyst, data scientist, data engineer, or similar positions
- 2+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala or others.)
Preferred Qualifications
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Master's or Ph.D degree in a STEM field
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