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- Tasks: Build robust data models and optimise the Data Warehouse using Snowflake.
- Company: Join Visa, a leading global payments technology company.
- Benefits: Enjoy a hybrid work environment with flexibility and competitive salary.
- Other info: Great opportunity for career growth in a dynamic tech environment.
- Why this job: Make an impact on data management and collaborate with diverse teams.
- Qualifications: Experience in Data Modelling, ETL projects, and proficiency in Python or Java.
The predicted salary is between 60000 - 80000 £ per year.
Visa is looking for a Senior Data Engineer to contribute to our Data Engineering team in London. The role involves building robust data models in Snowflake, optimizing the Data Warehouse, and establishing best practices for data management.
Key qualifications include:
- Experience in Data Modelling
- ETL projects
- Proficiency in Python or Java
This is a hybrid position, offering flexibility in the working environment and requires strong collaboration skills with multidisciplinary teams.
Senior Data Engineer — Data Platform & Cost Optimization in London employer: Visa
Contact Detail:
Visa Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer — Data Platform & Cost Optimization in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Visa on LinkedIn. A friendly chat can give us insider info about the team and the role, plus it shows our genuine interest.
✨Tip Number 2
Prepare for the interview by brushing up on your data modelling and ETL skills. We should be ready to discuss specific projects where we’ve optimised data warehouses or built robust data models in Snowflake.
✨Tip Number 3
Show off our collaboration skills! Think of examples where we’ve worked with multidisciplinary teams. It’s all about demonstrating how we can fit into their culture and contribute effectively.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure our application gets noticed. Plus, we can tailor our application to highlight our experience in Python or Java, which is key for this role.
We think you need these skills to ace Senior Data Engineer — Data Platform & Cost Optimization in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Data Modelling and ETL projects. We want to see how your skills align with the role, so don’t be shy about showcasing your proficiency in Python or Java!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Senior Data Engineer position and how you can contribute to our Data Engineering team. Let us know what makes you a great fit!
Showcase Collaboration Skills: Since this role involves working with multidisciplinary teams, make sure to mention any relevant experiences where you’ve successfully collaborated with others. We love seeing teamwork in action!
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’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Visa
✨Know Your Data Inside Out
Make sure you brush up on your data modelling skills and be ready to discuss your experience with Snowflake. Prepare examples of how you've built robust data models and optimised data warehouses in previous roles.
✨Showcase Your ETL Expertise
Be prepared to talk about your experience with ETL projects. Have specific examples ready that demonstrate your ability to design and implement efficient ETL processes, as this will be crucial for the role.
✨Demonstrate Your Coding Skills
Since proficiency in Python or Java is key, make sure you can discuss your coding experience confidently. You might even want to prepare a small coding challenge or two to showcase your problem-solving skills during the interview.
✨Collaboration is Key
This role requires strong collaboration skills, so think of examples where you've worked effectively with multidisciplinary teams. Be ready to discuss how you communicate complex data concepts to non-technical stakeholders.