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- Tasks: Enhance data platforms with robust models and optimised warehousing.
- Company: Global payment technology leader focused on innovation.
- Benefits: Hybrid work, competitive salary, and opportunities for professional growth.
- Why this job: Join a forward-thinking team leveraging real-time analytics to make an impact.
- Qualifications: Degree in relevant field and expertise in data modelling and ETL.
- Other info: Collaborative environment with a focus on data quality and governance.
The predicted salary is between 48000 - 72000 £ per year.
A global payment technology company is seeking a Senior Data Engineer to enhance its data platform through robust data models and optimized data warehousing. The ideal candidate will have a degree and expertise in data modeling, ETL projects, and languages like Python and Java. Familiarity with AWS and database technologies like Snowflake is essential. This hybrid position demands collaboration across teams to ensure data quality and governance. Join a forward-thinking environment committed to leveraging real-time analytics.
Senior Data Engineer: Snowflake Platform & Data Ops in London employer: Visa Inc.
Contact Detail:
Visa Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer: Snowflake Platform & Data Ops in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Snowflake or AWS. 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 data models and ETL projects. This is your chance to demonstrate your expertise in Python and Java, so make it shine when you get the opportunity to discuss your work.
✨Tip Number 3
Prepare for the interview by brushing up on data governance and quality assurance practices. Be ready to share how you've collaborated with teams in the past to ensure data integrity—this is key for a role like this!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are proactive and engaged. Plus, it gives you a better chance of being noticed by our hiring team.
We think you need these skills to ace Senior Data Engineer: Snowflake Platform & Data Ops in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your expertise in data modeling, ETL projects, and your proficiency in Python and Java. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the job description. Mention your experience with Snowflake and AWS specifically, as this will show us you’re a perfect fit for our team.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon unless it’s relevant. We appreciate a well-structured application that gets straight to the point!
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 Inc.
✨Know Your Data Inside Out
Make sure you brush up on your data modelling and ETL project experience. Be ready to discuss specific projects where you've used Snowflake, Python, or Java. Highlight how your contributions improved data quality or efficiency.
✨Showcase Your Collaboration Skills
Since this role involves working across teams, prepare examples of how you've successfully collaborated in the past. Think about times when you ensured data governance or quality through teamwork, and be ready to share those stories.
✨Familiarise Yourself with AWS
As familiarity with AWS is essential, make sure you can talk about your experience with it. Brush up on any relevant services you've used and be prepared to explain how they integrate with Snowflake and your data operations.
✨Prepare for Real-Time Analytics Questions
Given the focus on leveraging real-time analytics, think about how you've implemented or optimised analytics solutions in previous roles. Be ready to discuss the impact of these solutions on business decisions and outcomes.