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- Tasks: Build and scale data pipelines while ensuring data reliability and performance.
- Company: Dynamic tech company based in London with a hybrid work model.
- Benefits: Competitive salary of £70,000, flexible working, and opportunities for growth.
- Other info: Collaborative environment with a focus on professional development.
- Why this job: Join a team where your work directly impacts data-driven decisions and innovations.
- Qualifications: 2-5 years in Data Engineering with strong Python and SQL skills.
The predicted salary is between 70000 - 70000 £ per year.
Location: London (Hybrid 1 Day PW)
Salary: £70,000
About the Role
We’re looking for a Data Engineer to help build and scale our data platform. You’ll design pipelines, support analytics and ML use cases, and ensure data is reliable and production-ready.
What You’ll Do
- Build and maintain scalable ETL/ELT data pipelines
- Work with stakeholders to deliver clean, usable datasets
- Optimise data systems for performance and reliability
- Implement data quality checks and monitoring
- Support and develop our GCP data infrastructure
What We’re Looking For
- 2–5 years’ experience in Data Engineering
- Strong Python and SQL skills
- Hands-on experience with Google Cloud Platform (GCP)
- Experience with data warehousing and pipeline tools
- Strong problem-solving and collaboration skills
If this is of interest please apply and I will call to discuss.
Data Engineer in City of London employer: Switch Tech Talent
Contact Detail:
Switch Tech Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your Python and SQL skills, and be ready to discuss your experience with GCP. Practising common interview questions can really boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Data Engineer in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Data Engineering, especially with Python, SQL, and GCP. We want to see how your skills match what we’re looking for, so don’t be shy about showcasing relevant projects!
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 team. Keep it concise but engaging – we love a good story!
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in previous roles. We value strong problem-solving abilities, so share specific instances where you’ve made an impact!
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 Switch Tech Talent
✨Know Your Tech Stack
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss specific projects where you've used these technologies, especially in relation to building ETL/ELT pipelines.
✨Showcase Your GCP Experience
Since the role involves working with Google Cloud Platform, prepare to talk about your hands-on experience with GCP. Highlight any specific tools or services you've used and how they contributed to your data engineering projects.
✨Problem-Solving Scenarios
Expect to face some problem-solving questions during the interview. Think of examples from your past work where you encountered challenges in data systems and how you optimised them for performance and reliability.
✨Collaboration is Key
This role requires working closely with stakeholders. Be prepared to discuss how you've collaborated with others in previous roles to deliver clean, usable datasets and how you handle feedback and communication.