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- Tasks: Build and maintain scalable data pipelines using Airflow and dbt.
- Company: Fast-growing B2B financial services business based in London.
- Benefits: Competitive salary, remote/hybrid work options, and a dynamic team environment.
- Other info: Collaborate with analysts and data scientists in an Agile/Scrum environment.
- Why this job: Tackle interesting engineering challenges with valuable financial data in a modern cloud-native stack.
- Qualifications: Proven data engineering experience with strong Python, SQL, and AWS 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.
Senior Data Engineer - Remote/Hybrid employer: Kinvr Digital
Contact Detail:
Kinvr Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer - Remote/Hybrid
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work in 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 have loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Senior Data Engineer - Remote/Hybrid
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! Tell us why you’re excited about the opportunity and how your background makes you a great fit for our data platform team. Keep it engaging and personal.
Showcase Your Problem-Solving Skills: We love engineers who can tackle interesting problems! In your application, mention specific challenges you've faced in data engineering and how you approached them. This will help us see your thought process.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Kinvr Digital
✨Know Your Tech Stack
Make sure you’re well-versed in AWS, Python, and SQL. Brush up on your knowledge of Airflow and dbt too, as these are crucial for the role. Be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific engineering challenges you've faced, especially those related to data infrastructure. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your contributions.
✨Understand the Business Context
Familiarise yourself with the financial services industry and the importance of data governance. Being able to discuss how clean data impacts business decisions will show that you understand the bigger picture.
✨Emphasise Collaboration
Since the role involves working with analysts and data scientists, be prepared to discuss your experience in Agile/Scrum environments. Share examples of how you’ve successfully collaborated with cross-functional teams to deliver results.