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- Tasks: Develop and maintain data pipelines in a fast-paced, agile environment.
- Company: Leading tech firm based in Leeds with a focus on innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative teams and dynamic projects await you!
- Why this job: Make a meaningful impact by delivering modern data solutions for clients.
- Qualifications: Experience in Python, SQL, and cloud platforms like AWS, Azure, or GCP.
The predicted salary is between 45000 - 55000 £ per year.
A leading tech firm based in Leeds is seeking a Data Engineer to develop and maintain data pipelines in an agile environment. The ideal candidate will have solid experience in Python, SQL, and cloud platforms such as AWS, Azure, or GCP.
Responsibilities include:
- Working closely with multi-disciplinary teams to deliver modern data platforms
- Translating business needs into robust data products
This role promises opportunities for professional growth and meaningful impact on clients' lives.
Data Engineer: DataOps, Cloud Pipelines & Data Products employer: AND Digital
Contact Detail:
AND Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer: DataOps, Cloud Pipelines & Data Products
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or attend local 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, projects, or any cool stuff you've built using Python, SQL, or cloud platforms. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for those interviews! Brush up on common data engineering questions and be ready to discuss how you've tackled challenges in previous roles. Practice makes perfect, so consider mock interviews with friends.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Data Engineer: DataOps, Cloud Pipelines & Data Products
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and cloud platforms like AWS, Azure, or GCP. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how you can contribute to our agile environment. Let us know how you translate business needs into data products.
Showcase Your Teamwork Skills: Since this role involves working closely with multi-disciplinary teams, highlight any collaborative projects you've been part of. We love seeing how you’ve worked with others to deliver successful data solutions!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It’s the best way for us to receive your application and get to know you better!
How to prepare for a job interview at AND Digital
✨Know Your Tech Stack
Make sure you brush up on your Python, SQL, and cloud platforms like AWS, Azure, or GCP. Be ready to discuss specific projects where you've used these technologies, as this will show your practical experience and understanding of the tools.
✨Understand Agile Methodologies
Since the role is in an agile environment, it’s crucial to familiarise yourself with agile principles. Be prepared to talk about how you've worked in agile teams before and how you adapt to changing requirements.
✨Showcase Your Collaboration Skills
This position involves working closely with multi-disciplinary teams, so highlight your teamwork experiences. Think of examples where you successfully collaborated with others to deliver data solutions that met business needs.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving skills, especially related to data pipelines and products. Practice articulating your thought process when tackling complex data challenges, as this will demonstrate your analytical abilities.