Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and maintain real-time data pipelines with high-volume datasets.
- Company: Dynamic data solutions company based in London.
- Benefits: Competitive salary, flexible working hours, and opportunities for career advancement.
- Other info: Exciting projects with machine learning applications and a collaborative environment.
- Why this job: Join a cutting-edge team and elevate your data engineering skills.
- Qualifications: 3+ years in data engineering, proficient in Python and Rust.
The predicted salary is between 50000 - 60000 £ per year.
A data solutions company in London is seeking a skilled Data Engineer to work with high-volume datasets and cutting-edge technologies. In this role, you will build and maintain data pipelines, integrate real-time data feeds, and support machine learning applications.
The ideal candidate has:
- Over 3 years of experience in data engineering
- Strong proficiency in Python and Rust
- Hands-on experience with AWS, Linux, and Docker
If you are ready to advance your data engineering career, we want to hear from you!
Data Engineer – Real-Time, Scalable Data Pipelines employer: Consortia Group
Contact Detail:
Consortia Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer – Real-Time, Scalable Data Pipelines
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the hunt for a new role. You never know who might have a lead or can refer you to a position that’s not even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving real-time data pipelines or machine learning applications. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and Rust skills. Practice coding challenges and be ready to discuss your experience with AWS, Linux, and Docker. We want you to feel confident when it comes to showcasing your expertise!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you who are eager to advance their careers in data engineering.
We think you need these skills to ace Data Engineer – Real-Time, Scalable Data Pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data engineering, especially your work with Python, Rust, and AWS. We want to see how your skills match the job description, so don’t be shy about showcasing your 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 your background makes you a perfect fit for our team. Let us know what excites you about working with real-time data feeds.
Showcase Your Projects: If you've worked on any cool data pipelines or machine learning applications, make sure to mention them in your application. We love seeing practical examples of your work, so include links or descriptions that highlight your hands-on experience.
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. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at Consortia Group
✨Know Your Tech Stack
Make sure you brush up on your Python and Rust skills before the interview. Be ready to discuss specific projects where you've used these languages, especially in building data pipelines or integrating real-time data feeds.
✨Showcase Your Experience with AWS and Docker
Prepare examples of how you've utilised AWS services and Docker in your previous roles. Companies love to hear about real-world applications, so think of scenarios where you solved problems or improved processes using these technologies.
✨Understand the Company’s Data Needs
Research the company and its data solutions. Familiarise yourself with their products and services, and be prepared to discuss how your skills can help them tackle their specific challenges in handling high-volume datasets.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about their current data projects, team dynamics, or future technology plans. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.