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 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. 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
✨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 and data models. Having tangible examples of your expertise can really impress hiring managers and set you apart from the crowd.
✨Tip Number 3
Prepare for the technical interview! Brush up on your AWS knowledge and be ready to discuss how you've optimised data quality and performance in past projects. We want to see your problem-solving skills in action!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the team at View, Inc. and contributing to their mission.
We think you need these skills to ace AI-Driven Data Engineer: Scalable Pipelines & Data Quality
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 optimising data processes for our marketplace.
Showcase Your Projects:Include specific examples of projects where you've developed data models or improved data quality. This helps us understand your hands-on experience and how you can contribute to our team.
Be Clear and Concise:When writing your cover letter, keep it straightforward. We appreciate clarity, so get to the point about why you're a great fit for the Data Engineer role and how you can help us build the best home improvement marketplace.
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 from 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, think of examples where you successfully collaborated with cross-functional teams. Highlight your communication skills and how you’ve contributed to engineering standards in those settings.
✨Ask Insightful Questions
Prepare thoughtful questions about View, Inc.'s data strategy and how they ensure data quality. This shows your genuine interest in the company and the role, plus it gives you a chance to assess if the company culture aligns with your values.
