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- Tasks: Build and operate data pipelines while ensuring data quality and lineage.
- Company: Cape.io, a forward-thinking tech company in Greater London.
- Benefits: Competitive salary, learning culture, and potential for career advancement.
- Other info: Exciting opportunity to grow into a lead position in a dynamic environment.
- Why this job: Collaborate with AI/ML engineers and shape the future of data.
- Qualifications: 3–5 years experience, strong Python and SQL skills, and modern data stack knowledge.
The predicted salary is between 50000 - 60000 £ per year.
Cape.io (formerly Peach) is seeking a Data Engineer in Greater London to build and operate data pipelines, establish data quality, and set up lineage.
Candidates should have 3–5 years of experience, solid Python and SQL skills, and hands-on experience with the modern data stack, including Airflow and AWS or GCP.
This role offers collaboration with AI/ML engineers and a potential path to a lead position. Competitive salary and a culture of learning are included.
Data Platform Engineer: Pipelines, Lineage & AI‑Ready Data employer: Cape.io (formerly Peach)
Contact Detail:
Cape.io (formerly Peach) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Platform Engineer: Pipelines, Lineage & AI‑Ready Data
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Cape.io. A friendly chat can sometimes lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. This is your chance to demonstrate your Python and SQL prowess, so make it shine!
✨Tip Number 3
Prepare for the interview by brushing up on Airflow and cloud platforms like AWS or GCP. We want you to feel confident discussing your hands-on experience with these tools.
✨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.
We think you need these skills to ace Data Platform Engineer: Pipelines, Lineage & AI‑Ready Data
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and SQL skills in your application. We want to see how you've used these tools in real projects, especially with data pipelines and the modern data stack.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific requirements of the Data Platform Engineer role. We love seeing candidates who understand what we’re looking for.
Share Your Experience: If you’ve got hands-on experience with Airflow, AWS, or GCP, make sure to mention it! We’re keen on candidates who can demonstrate their practical knowledge and how it relates to the job.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Cape.io (formerly Peach)
✨Know Your Data Stack
Make sure you’re well-versed in the modern data stack, especially tools like Airflow and cloud platforms such as AWS or GCP. Brush up on how these technologies work together to build efficient data pipelines, as this will likely come up during your interview.
✨Showcase Your Python and SQL Skills
Prepare to discuss your experience with Python and SQL in detail. Be ready to share specific examples of projects where you’ve used these languages to solve problems or improve data quality. Practising coding challenges can also help you feel more confident.
✨Understand Data Lineage and Quality
Familiarise yourself with concepts of data lineage and quality assurance. Be prepared to explain how you would establish data quality in a pipeline and why it’s important. This shows that you understand the bigger picture of data management.
✨Collaborate and Communicate
Since this role involves working with AI/ML engineers, highlight your teamwork and communication skills. Think of examples where you’ve successfully collaborated on projects, and be ready to discuss how you can contribute to a culture of learning within the team.