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- Tasks: Own and modernise data pipelines for a high-growth payments platform.
- Company: Join a dynamic team focused on data quality and reliability.
- Benefits: Competitive salary, learning budget, and conference allowance.
- Other info: Work remotely within UK or EU time zones with excellent career growth.
- Why this job: Make a real impact while mentoring engineers in a remote role.
- Qualifications: 5+ years in data engineering with Python, DBT, and Airflow experience.
The predicted salary is between 70000 - 130000 £ per year.
Own pipelines and analytics for a high growth payments platform. You will modernize the stack and mentor engineers on data quality and reliability.
Responsibilities:
- Design and maintain ELT with DBT and Airflow
- Scale batch and streaming with Spark
- Define data contracts with product and engineering
- Improve lineage, testing and observability
Requirements:
- 5+ years in data engineering with Python
- DBT and Airflow in production
- Experience with Spark or similar frameworks
- Great communication and documentation habits
- Remote within UK or EU time zones
- Learning budget and conference allowance
Senior Data Engineer Remote EU/USA and UK Python, Spark, Airflow, DBT £70-130K base • Permanent[...] in London employer: FullRemoteTalent
Contact Detail:
FullRemoteTalent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer Remote EU/USA and UK Python, Spark, Airflow, DBT £70-130K base • Permanent[...] in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Python, DBT, and Airflow. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Spark and ELT processes. 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 your communication skills. Be ready to explain complex concepts clearly, as great communication is key in this role. Practice common interview questions related to data quality and reliability.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got 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 EU/USA and UK Python, Spark, Airflow, DBT £70-130K base • Permanent[...] in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, DBT, and Airflow. We want to see how you've used these tools in real-world scenarios, so don’t hold back on the details!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about data engineering and how you can contribute to our high-growth payments platform. Keep it engaging and relevant!
Showcase Your Projects: If you've worked on any cool projects involving Spark or similar frameworks, make sure to mention them. We love seeing practical examples of your skills and how you've tackled challenges in the past.
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 FullRemoteTalent
✨Know Your Tech Stack
Make sure you’re well-versed in Python, DBT, Airflow, and Spark. Brush up on your experience with these tools, as you'll likely be asked to discuss how you've used them in past projects. Be ready to share specific examples of how you've designed and maintained ELT processes.
✨Showcase Your Problem-Solving Skills
Prepare to discuss challenges you've faced in data engineering and how you overcame them. Companies love candidates who can demonstrate their ability to troubleshoot and innovate, especially when it comes to improving data quality and reliability.
✨Communicate Clearly
Since great communication is a requirement, practice explaining complex technical concepts in simple terms. You might be asked to describe your approach to defining data contracts or improving observability, so clarity is key!
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data strategy and team dynamics. This shows your genuine interest in the role and helps you assess if the company culture aligns with your values, especially regarding mentorship and collaboration.