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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 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.
Data Engineer (AWS) · Hybrid Remote employer: Kinvr Digital
Contact Detail:
Kinvr Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (AWS) · Hybrid Remote
✨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 building data pipelines or working with cloud infrastructure—this will help you shine during technical interviews.
✨Tip Number 4
Don't forget to apply through our website! We often have exclusive listings and can help you connect directly with hiring managers. Plus, it shows you're serious about landing that Data Engineer role!
We think you need these skills to ace Data Engineer (AWS) · Hybrid Remote
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with AWS, Python, and SQL, and don’t forget to mention any work you've done with data pipelines or cloud infrastructure.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your skills align with the company's goals. Be sure to mention your experience in Agile/Scrum environments.
Showcase Relevant Projects: If you've worked on any projects that involved building scalable data pipelines or modernising data infrastructure, make sure to include them. This will show us that you have hands-on experience with the challenges we face.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
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, 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 and how you tackled them. This is a great opportunity to demonstrate your analytical thinking and ability to modernise data infrastructures.
✨Understand the Business Context
Familiarise yourself with the financial services industry and the importance of data governance. Being able to relate your technical skills to business outcomes will impress the interviewers.
✨Emphasise Collaboration
Since the role involves working with analysts and data scientists, be prepared to discuss your experience in Agile/Scrum environments. Highlight examples where you’ve successfully collaborated with cross-functional teams to deliver clean and reliable data.