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- Tasks: Design and maintain data pipelines while translating business needs into data solutions.
- Company: Fast-growing startup in Greater London with a focus on innovation.
- Benefits: Competitive salary, meaningful share options, and 32 days holiday.
- Other info: Hybrid work model with opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of data architecture.
- Qualifications: Experience in data engineering, strong SQL skills, and familiarity with AWS and Docker.
The predicted salary is between 50000 - 65000 £ per year.
A fast-growing startup in Greater London is seeking a Data & Analytics Engineer to own data architecture and ensure the business can reliably query it. You will design and maintain data pipelines, working closely with non-technical stakeholders to translate business needs into data solutions.
Ideal candidates have experience in data engineering and strong SQL skills, along with familiarity with key tools like AWS and Docker.
Competitive salary and meaningful share options are offered in addition to 32 days holiday.
Data & Analytics Engineer — Hybrid, AI-Ready Data Platform employer: Harper
Contact Detail:
Harper Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data & Analytics Engineer — Hybrid, AI-Ready Data Platform
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving SQL, AWS, or Docker. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you, and applying directly can sometimes give you a better chance of standing out.
We think you need these skills to ace Data & Analytics Engineer — Hybrid, AI-Ready Data Platform
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering and SQL skills. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or tools like AWS and Docker.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data & Analytics Engineer position and how you can help us build a robust data architecture. Keep it concise but impactful!
Showcase Your Problem-Solving Skills: In your application, give examples of how you've translated business needs into data solutions. We love candidates who can bridge the gap between technical and non-technical stakeholders, so share those experiences!
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Harper
✨Know Your Data Tools
Make sure you brush up on your knowledge of AWS and Docker before the interview. Be ready to discuss how you've used these tools in past projects, as this will show your practical experience and understanding of the tech stack.
✨Speak Their Language
Since you'll be working with non-technical stakeholders, practice explaining complex data concepts in simple terms. This will demonstrate your ability to bridge the gap between technical and non-technical teams, which is crucial for the role.
✨Showcase Your SQL Skills
Prepare to tackle some SQL questions or even a live coding challenge. Brush up on your query writing skills and think about how you can optimise queries for performance, as this will highlight your expertise in data engineering.
✨Understand the Business Needs
Research the startup's business model and think about how data solutions can drive their success. Being able to articulate how your work as a Data & Analytics Engineer can directly impact their goals will set you apart from other candidates.