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- Tasks: Design and maintain scalable data pipelines while ensuring data quality.
- Company: Fast-growing tech startup in Greater London with a vibrant culture.
- Benefits: Competitive salary, flexible working hours, and paid volunteer days.
- Why this job: Join a dynamic team and shape the future of data engineering.
- Qualifications: 7+ years in data engineering, expertise in SQL and Python.
- Other info: Exciting opportunities for growth in a collaborative environment.
The predicted salary is between 60000 - 105000 £ per year.
A fast-growing tech startup in Greater London is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines. You will contribute to the data platform infrastructure while ensuring data quality and governance.
Ideal candidates have over 7 years of experience in data engineering, deep expertise in SQL and Python, and hands-on experience with tools like dbt and Kubernetes.
This role offers a competitive salary and numerous employee benefits, including flexible working hours and paid volunteer days.
Senior Data Engineer: Pipelines, Governance & Platform in London employer: Goodstack
Contact Detail:
Goodstack Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer: Pipelines, Governance & Platform in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work in data engineering. A friendly chat can lead to referrals or insider info about job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Python, and tools like dbt and Kubernetes. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. We recommend practising coding challenges and discussing your past experiences with data governance and pipeline design.
✨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 are proactive and engaged with our platform.
We think you need these skills to ace Senior Data Engineer: Pipelines, Governance & Platform in London
Some tips for your application 🫡
Show Off Your Experience: When you're writing your application, make sure to highlight your 7+ years of experience in data engineering. We want to see how your background aligns with the role, so don’t hold back on showcasing your expertise in SQL and Python!
Tailor Your Application: Take a moment to customise your application for us. Mention specific projects where you've designed or maintained data pipelines, and how you’ve ensured data quality and governance. This will help us see how you fit into our team!
Be Clear and Concise: We appreciate clarity! Keep your application straightforward and to the point. Use bullet points if necessary to make it easy for us to read through your skills and experiences.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, we love seeing candidates who follow instructions!
How to prepare for a job interview at Goodstack
✨Know Your Tech Stack
Make sure you’re well-versed in SQL and Python, as these are crucial for the role. Brush up on your knowledge of dbt and Kubernetes too, as you might be asked to discuss how you've used these tools in past projects.
✨Showcase Your Experience
With over 7 years in data engineering, you’ll want to highlight specific projects where you designed and maintained data pipelines. Be ready to share examples that demonstrate your expertise in data governance and quality assurance.
✨Prepare for Scenario Questions
Expect questions that assess your problem-solving skills. Think about challenges you’ve faced in previous roles and how you overcame them, especially in relation to data pipeline scalability and governance.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the company’s data platform infrastructure and how they ensure data quality. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.