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- Tasks: Build and maintain scalable data pipelines using Airflow and dbt on AWS.
- Company: Fast-growing B2B financial services business based in London.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborative Agile/Scrum environment with a focus on data quality and governance.
- Why this job: Tackle interesting engineering challenges while modernising data infrastructure.
- Qualifications: Proven experience in data engineering with strong Python and SQL skills.
The predicted salary is between 75000 - 105000 £ per year.
I'm working with a fast-growing B2B finserv business based in London, and they're looking for a Senior Data Engineer to join their data platform team.
This is a genuinely interesting engineering problem — they're sitting on a large volume of valuable financial data and are in the process of modernising their data infrastructure, moving away from legacy systems towards a scalable, cloud-native stack.
- Building and maintaining scalable data pipelines using Airflow and dbt
- Working across AWS cloud infrastructure
- Collaborating with analysts and data scientists to deliver reliable, clean data for downstream reporting and business decision-making
- Contributing to data quality, governance, and best practices across the team
Proven data engineering experience with strong Python and SQL.
Solid AWS experience.
Comfortable working in Agile/Scrum environments.
AWS Data Engineer - Hybrid/Remote in City of London employer: Kinvr Digital
Contact Detail:
Kinvr Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Data Engineer - Hybrid/Remote in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work with AWS or data engineering. 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 projects, especially those involving AWS, Python, and SQL. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when tackling engineering problems, as this will demonstrate your expertise and problem-solving skills.
✨Tip Number 4
Don't forget to apply through our website! We often have exclusive listings and it’s a great way to get noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AWS Data Engineer - Hybrid/Remote in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, Python, and SQL. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how your background makes you a perfect fit for our data platform team. Let your personality come through!
Showcase Your Problem-Solving Skills: Since we’re tackling interesting engineering problems, share examples of how you've approached challenges in the past. We love seeing how you think and what solutions you’ve implemented!
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 Kinvr Digital
✨Know Your AWS Inside Out
Make sure you brush up on your AWS knowledge before the interview. Familiarise yourself with the specific services mentioned in the job description, like S3, Redshift, and Lambda. Being able to discuss how you've used these services in past projects will show that you're not just a theoretical expert but someone who can apply their knowledge practically.
✨Showcase Your Data Pipeline Skills
Prepare to talk about your experience with building and maintaining data pipelines, especially using tools like Airflow and dbt. Have specific examples ready that demonstrate your ability to create scalable solutions and how they improved data flow or quality in previous roles.
✨Collaboration is Key
Since this role involves working closely with analysts and data scientists, be ready to discuss how you've collaborated with cross-functional teams in the past. Highlight any Agile/Scrum experiences you have, as this will show that you can thrive in a dynamic environment and contribute to team success.
✨Demonstrate Your Problem-Solving Skills
Expect to face some technical challenges during the interview. Prepare for scenario-based questions where you might need to solve a data engineering problem on the spot. Practising these types of questions can help you articulate your thought process clearly and showcase your analytical skills.