Data Engineer: Remote/Hybrid, Build Predictive Data Pipelines in Burgess Hill

Data Engineer: Remote/Hybrid, Build Predictive Data Pipelines in Burgess Hill

Burgess Hill Full-Time 50000 - 60000 £ / year (est.) No working from home possible
Edwards Vacuum

At a Glance

  • Tasks: Build and maintain ETL pipelines for predictive data insights.
  • Company: Join Edwards Vacuum, a fast-growing transformation team.
  • Benefits: Enjoy remote/hybrid work, competitive salary, and career growth.
  • Other info: Be part of a dynamic team driving innovation in data.
  • Why this job: Make an impact by optimising data for better customer outcomes.
  • Qualifications: Experience in data engineering and strong collaboration skills.

The predicted salary is between 50000 - 60000 £ per year.

Edwards Vacuum is seeking a Data Engineer to join a fast-growing transformation team. You will build and maintain ETL pipelines and data lakes, enabling data-driven ML insights to predict asset performance and improve customer outcomes.

You will collaborate with Data Scientists and analytics teams, ensure pipeline reliability, and optimize performance while communicating findings to stakeholders across the organization.

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Data Engineer: Remote/Hybrid, Build Predictive Data Pipelines in Burgess Hill employer: Edwards Vacuum

As a Lead Engineer – NPI & Engineering at our Global Technology Centre in Burgess Hill, you will thrive in a collaborative and innovative work culture that prioritises employee growth and development. We offer a hybrid working arrangement, competitive compensation, and a commitment to embedding serviceability into product design, ensuring that your contributions directly enhance customer experience and product quality. Join us to be part of a team that values your expertise and fosters meaningful career advancement in the dynamic field of semiconductor services.

Edwards Vacuum

Contact Details:

Edwards Vacuum Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Engineer: Remote/Hybrid, Build Predictive Data Pipelines in Burgess Hill

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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!

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Craft a Tailored Cover Letter:For a full-time role at Edwards Vacuum, 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 Edwards Vacuum. 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 Edwards Vacuum

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!

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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

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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.