At a Glance
- Tasks: Design and improve data workflows while managing critical data pipelines.
- Company: Join Kpler, a forward-thinking company in the heart of Greater London.
- Benefits: Enjoy competitive pay, inclusive culture, and opportunities for mentorship.
- Other info: Be part of an inclusive team dedicated to pushing data boundaries.
- Why this job: Make a real impact on refinery operations with innovative data solutions.
- Qualifications: Strong coding skills and experience with data platforms like Kafka or Spark.
The predicted salary is between 60000 - 80000 € per year.
Kpler is seeking a Senior Data Engineer in Greater London to manage data pipelines and backend systems critical to refinery operations. The role involves:
- Designing, building, and improving data workflows
- Collaborating with cross-functional teams to ensure pipeline reliability
- Mentoring junior engineers
Candidates should have:
- A strong coding background
- Experience with data platforms
- Familiarity with streaming architectures like Kafka or Spark
Join an inclusive team dedicated to innovative data solutions.
Senior Backend Engineer: Data Pipelines & Platform in London employer: Kpler
Kpler is an exceptional employer that fosters a collaborative and inclusive work culture in the heart of Greater London. With a strong emphasis on innovation, employees are encouraged to grow their skills through mentorship and hands-on experience with cutting-edge data technologies. The company offers competitive benefits and a dynamic environment where your contributions directly impact refinery operations and the broader energy sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Backend Engineer: Data Pipelines & Platform in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Kpler on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio or GitHub repository showcasing your projects, especially those involving data pipelines or streaming architectures like Kafka or Spark. This will help us see your coding chops in action.
✨Tip Number 3
Ace the interview by practising common technical questions related to backend systems and data workflows. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect directly with us.
We think you need these skills to ace Senior Backend Engineer: Data Pipelines & Platform in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your coding background and experience with data platforms in your application. 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 specific requirements mentioned in the job description. We love seeing candidates who take the time to connect their experience with what we’re looking for.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your key achievements and experiences shine through without unnecessary fluff.
Apply Through Our Website:We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role!
How to prepare for a job interview at Kpler
✨Know Your Data Pipelines
Make sure you brush up on your knowledge of data pipelines and backend systems. Be ready to discuss your experience with designing and improving workflows, as well as any specific projects you've worked on that relate to refinery operations.
✨Show Off Your Coding Skills
Since a strong coding background is essential for this role, prepare to demonstrate your coding skills during the interview. You might be asked to solve a problem or explain your thought process, so practice coding challenges relevant to data engineering.
✨Familiarise Yourself with Streaming Architectures
Get comfortable discussing streaming architectures like Kafka or Spark. Be prepared to share examples of how you've used these technologies in past projects and how they can enhance data pipeline reliability.
✨Emphasise Collaboration and Mentorship
This role involves working with cross-functional teams and mentoring junior engineers. Think of examples where you've successfully collaborated with others or helped develop less experienced team members, and be ready to share those stories.
