Product Analytics Data Engineer: Scale Impact & Insights in City of Westminster

Product Analytics Data Engineer: Scale Impact & Insights in City of Westminster

City of Westminster Full-Time 63000 - 77000 £ / year (est.) No working from home possible
M

At a Glance

  • Tasks: Design and build large-scale datasets to support billions of users and businesses.
  • Company: Join Meta, a leader in social media and technology innovation.
  • Benefits: Competitive salary, flexible work options, and opportunities for growth.
  • Other info: Collaborative environment with a focus on innovation and career development.
  • Why this job: Shape impactful data products that drive insights across popular platforms.
  • Qualifications: Strong background in data engineering and AI workflows required.

The predicted salary is between 63000 - 77000 £ per year.

Meta seeks a Data Engineer to shape data products across Facebook, Instagram, Messenger, Whats App, Reality Labs, and Threads.

You will design and build large-scale datasets and visualizations to support billions of users and hundreds of millions of businesses.

You will collaborate with software, data science, and product teams to deliver scalable data solutions, ensure data quality, and drive product insights.

A strong background in data engineering and AI-enabled workflows is expected.

#J-18808-Ljbffr

Product Analytics Data Engineer: Scale Impact & Insights in City of Westminster employer: META

Meta is an exceptional employer that fosters a dynamic and innovative work culture, where creativity and collaboration thrive. Located in a vibrant tech hub, employees benefit from extensive growth opportunities, competitive compensation, and a commitment to work-life balance, making it an ideal place for those looking to make a meaningful impact in the advertising landscape.

M

Contact Details:

META Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Product Analytics Data Engineer: Scale Impact & Insights in City of Westminster

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like META!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Product Analytics Data Engineer: Scale Impact & Insights at META.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like META.

Apply Directly through Our Website

When you find a suitable opening like Product Analytics Data Engineer: Scale Impact & Insights at META, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Product Analytics Data Engineer: Scale Impact & Insights in City of Westminster

Data Engineering
AI-enabled Workflows
Large-scale Dataset Design
Data Visualisation
Collaboration with Software Teams
Collaboration with Data Science Teams
Collaboration with Product Teams

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at META, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at META. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at META

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at META!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.