Data Engineer β€” Build & Optimize Pipelines (Flexible Hours) in London

Data Engineer β€” Build & Optimize Pipelines (Flexible Hours) in London

London Full-Time 65250 - 79750 Β£ / year (est.) Home office (partial)
Ogury

At a Glance

  • Tasks: Build and optimise data pipelines for efficient reporting and insights.
  • Company: Join Ogury, a leading data-driven company in the UK.
  • Benefits: Flexible hours, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on innovation and collaboration.
  • Why this job: Make data accessible and impactful for clients while collaborating with diverse teams.
  • Qualifications: Hands-on experience with data pipelines and a passion for data accessibility.

The predicted salary is between 65250 - 79750 Β£ per year.

Ogury is seeking a motivated Data Engineer to join our Data Reporting team in the UK.

You will organize and maintain the data stack, ensuring data availability and efficient reporting for internal and external clients such as Ogury One.

You will collaborate with data platform, persona, and SSP teams to optimize architecture, model data, and deliver actionable insights.

This role suits someone with hands-on experience in pipelines and a passion for making data accessible to business users.

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Data Engineer β€” Build & Optimize Pipelines (Flexible Hours) in London employer: Ogury

Ogury is an exceptional employer that champions innovation and collaboration in the dynamic field of digital advertising. With a hybrid work model, employees enjoy a balanced work-life environment while being part of a forward-thinking team that values personal growth and professional development. Located in Greater London, Ogury offers unique opportunities to shape the future of CTV solutions, making it an ideal place for those looking to make a meaningful impact in their careers.

Ogury

Contact Details:

Ogury Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Data Engineer β€” Build & Optimize Pipelines (Flexible Hours) in London

✨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 Ogury!

✨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 Data Engineer β€” Build & Optimize Pipelines (Flexible Hours) at Ogury.

✨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 Ogury.

✨Apply Directly through Our Website

When you find a suitable opening like Data Engineer β€” Build & Optimize Pipelines (Flexible Hours) at Ogury, 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 Data Engineer β€” Build & Optimize Pipelines (Flexible Hours) in London

SQL
Data Pipeline Development
Python
Problem-Solving Skills
Data Engineering
API Integration
Communication Skills

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 Ogury, 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 Ogury. 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 Ogury

✨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 Ogury!

✨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.