Data Engineer, Product Analytics
Data Engineer, Product Analytics

Data Engineer, Product Analytics

Full-Time 43200 - 72000 £ / year (est.) No home office possible
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Meta

At a Glance

  • Tasks: Design and build scalable data solutions for Meta's family of apps.
  • Company: Join Meta, a leader in social technology and innovation.
  • Benefits: Competitive salary, comprehensive benefits, and opportunities for growth.
  • Why this job: Shape the future of products impacting billions globally.
  • Qualifications: 7+ years in data roles with strong SQL and programming skills.
  • Other info: Collaborative environment with mentorship and career advancement.

The predicted salary is between 43200 - 72000 £ per year.

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 some of the world's most extensive 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+ 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.

Data Engineering:

You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions, refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, with a focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.

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:
  • Conceptualize and own the data architecture for multiple large‑scale projects, while evaluating design and operational cost‑benefit tradeoffs within systems.
  • Create and contribute to frameworks that improve the efficacy of logging 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.
  • Define and manage Service Level Agreements for all data sets in allocated areas of ownership.
  • Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership.
  • Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains.
  • Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources.
  • 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.
  • Mentor team members by giving/receiving actionable feedback.
Minimum Qualifications:
  • Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent.
  • 7+ years of experience where the primary responsibility involves working with data (data analyst, data scientist, data engineer, or similar positions).
  • 7+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala or others).
Preferred Qualifications:
  • Master’s or Ph.D. degree in a STEM field.
About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps 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.

Data Engineer, Product Analytics employer: Meta

Meta is an exceptional employer that fosters a dynamic and innovative work culture, where Data Engineers play a pivotal role in shaping the future of technology across its extensive suite of applications. With a strong emphasis on collaboration, employee growth opportunities, and a commitment to data security and quality, Meta provides a unique environment for professionals to tackle complex challenges at an unparalleled scale. Employees benefit from competitive compensation, comprehensive benefits, and the chance to contribute to transformative projects that impact billions of users worldwide.
Meta

Contact Detail:

Meta Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Engineer, Product Analytics

✨Tip Number 1

Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your data projects, visualisations, and any cool stuff you've built. This gives potential employers a taste of what you can do.

✨Tip Number 3

Prepare for interviews by practising common data engineering questions. Get comfy with SQL queries and ETL processes, and be ready to discuss how you’ve tackled data challenges in the past.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.

We think you need these skills to ace Data Engineer, Product Analytics

Data Architecture
Data Modelling
SQL
ETL
Python
C++
C#
Scala
Data Visualisation
Data Security
Data Quality Management
Analytical Skills
Collaboration
Communication Skills
Mentoring

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with SQL, ETL, and data modelling, and don’t forget to showcase any relevant projects that demonstrate your analytical mindset and technical skills.

Craft a Compelling Cover Letter: Your cover letter is your chance to tell your story! Use it to explain why you’re passionate about data engineering and how your background aligns with the responsibilities outlined in the job description. Be sure to mention your collaborative experiences with product management and engineering teams.

Showcase Your Problem-Solving Skills: In your application, highlight specific examples where you've tackled complex data challenges. This could be through optimising data pipelines or creating scalable data models. We want to see how you approach problems and come up with innovative solutions!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!

How to prepare for a job interview at Meta

✨Know Your Data Inside Out

Before the interview, dive deep into your past projects involving data engineering. Be ready to discuss specific datasets you've worked with, the challenges you faced, and how you optimised them. This will show your technical prowess and analytical mindset, which are crucial for the role.

✨Master the Art of Storytelling with Data

Prepare to present your data-driven insights in a compelling way. Think about how you can turn raw data into a narrative that highlights its impact on product development or user experience. Practising this will help you communicate effectively and influence your interviewers.

✨Brush Up on SQL and ETL Techniques

Since the role requires extensive experience with SQL and ETL processes, make sure you're comfortable discussing these topics. Review common SQL queries and ETL patterns, and be prepared to solve problems on the spot. This will demonstrate your hands-on expertise and readiness for the job.

✨Collaborate and Communicate

Think about examples where you've successfully collaborated with cross-functional teams. Be ready to share how you’ve communicated complex data insights to non-technical stakeholders. This will highlight your ability to be a trusted strategic partner, which is key for the position.

Data Engineer, Product Analytics
Meta
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