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- Tasks: Enhance data architecture and support high-performance data pipelines.
- Company: Leading forecasting agency with a focus on employee well-being.
- Benefits: Flexible working environment and strong emphasis on professional development.
- Why this job: Join a dynamic team to optimise data flows and ensure quality.
- Qualifications: 5+ years of data engineering experience and expert SQL skills.
- Other info: Collaborate with data scientists and engineers in an innovative setting.
The predicted salary is between 43200 - 72000 £ per year.
A leading forecasting agency is looking for a Senior Data Engineer to enhance their data architecture and support high-performance data pipelines in London. The ideal candidate will have over 5 years of data engineering experience, expert-level SQL skills, and proficiency with Snowflake and Databricks. You will work closely with data scientists and engineers to optimize data flows and ensure data quality. The company offers a flexible working environment with a strong focus on employee well-being and development.
Senior Data Engineer: AI Pipelines & Cloud Data (London) employer: WGSN
Contact Detail:
WGSN Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer: AI Pipelines & Cloud Data (London)
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with AI pipelines or cloud data. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving SQL, Snowflake, and Databricks. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. We recommend practising with friends or using mock interview platforms to build your confidence and refine your answers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Data Engineer: AI Pipelines & Cloud Data (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, especially with SQL, Snowflake, and Databricks. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how you can contribute to our team. We love seeing enthusiasm and a bit of personality!
Showcase Your Problem-Solving Skills: In your application, mention specific challenges you've tackled in previous roles. We’re keen on candidates who can optimise data flows and ensure quality, so share examples that demonstrate your expertise.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you get the best experience possible. Plus, we can’t wait to hear from you!
How to prepare for a job interview at WGSN
✨Know Your Tech Inside Out
Make sure you brush up on your SQL skills and get familiar with Snowflake and Databricks. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your Data Pipeline Experience
Prepare to talk about your experience with data architecture and high-performance data pipelines. Think of examples that highlight your ability to optimise data flows and ensure data quality, as this is crucial for the role.
✨Collaborate Like a Pro
Since you'll be working closely with data scientists and engineers, be ready to discuss how you've collaborated in the past. Share examples of how you’ve contributed to team projects and how you handle feedback and differing opinions.
✨Emphasise Your Adaptability
With a flexible working environment, it’s important to show that you can adapt to different situations. Talk about times when you had to adjust your approach or learn new tools quickly to meet project demands.
