At a Glance
- Tasks: Build scalable data pipelines and ensure top-notch data quality for AI services.
- Company: Join View, Inc., the UK's leading home improvement marketplace.
- Benefits: Enjoy a competitive salary, annual bonuses, gym membership, and more perks.
- Other info: Collaborate with talented Data Scientists and Analysts in a vibrant work environment.
- Why this job: Make a real impact in a dynamic team while working with cutting-edge technology.
- Qualifications: Experience in data engineering and a passion for optimising data processes.
The predicted salary is between 50000 - 65000 € per year.
View, Inc. is seeking a Data Engineer to build the UK's leading home improvement marketplace. The role involves optimising ETL and ELT pipelines on AWS, developing data models for AI services, and ensuring data quality and performance.
Collaborate with Data Scientists, Analysts, and Product teams while contributing to engineering standards.
Benefits include a competitive salary, annual bonuses, gym membership, and other attractive perks.
AI-Driven Data Engineer: Scalable Pipelines & Data Quality in London employer: View, Inc.
View, Inc. is an exceptional employer that fosters a collaborative and innovative work culture, perfect for those passionate about transforming the home improvement marketplace in the UK. With a focus on employee growth, we offer competitive salaries, annual bonuses, and perks like gym memberships, ensuring our team thrives both professionally and personally in a dynamic environment.
StudySmarter Expert Advice🤫
We think this is how you could land AI-Driven Data Engineer: Scalable Pipelines & Data Quality in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at View, Inc. or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work on ETL/ELT pipelines or any AI-driven projects. This is your chance to demonstrate your expertise and passion for data engineering.
✨Tip Number 3
Prepare for the interview by brushing up on AWS services and data quality best practices. We want you to feel confident discussing how you can optimise pipelines and contribute to engineering standards.
✨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 that extra step to connect with us directly.
We think you need these skills to ace AI-Driven Data Engineer: Scalable Pipelines & Data Quality in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with ETL and ELT pipelines, especially on AWS. We want to see how your skills align with the role of an AI-Driven Data Engineer, so don’t hold back on 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 building data models for AI services and how you can contribute to our engineering standards. Keep it engaging and personal – we love to see your personality!
Showcase Collaboration Skills:Since this role involves working closely with Data Scientists, Analysts, and Product teams, make sure to mention any collaborative projects you've been part of. We value teamwork, so let us know how you’ve contributed to successful outcomes in the past.
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 don’t miss out on any important updates. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at View, Inc.
✨Know Your ETL and ELT Inside Out
Make sure you’re well-versed in optimising ETL and ELT pipelines, especially on AWS. Brush up on your technical skills and be ready to discuss specific projects where you've implemented these processes. This will show that you can hit the ground running.
✨Showcase Your Data Modelling Skills
Prepare to talk about your experience with developing data models for AI services. Bring examples of how your models improved data quality or performance in previous roles. This will demonstrate your ability to contribute effectively to the team.
✨Collaboration is Key
Since the role involves working closely with Data Scientists, Analysts, and Product teams, be ready to share examples of successful collaborations. Highlight how you’ve communicated complex data concepts to non-technical stakeholders, as this will showcase your teamwork skills.
✨Understand Engineering Standards
Familiarise yourself with engineering standards relevant to data engineering. Be prepared to discuss how you ensure quality and performance in your work. This shows that you value best practices and are committed to maintaining high standards in your projects.
