At a Glance
- Tasks: Build robust data pipelines and integrate machine learning outputs into products.
- Company: Fast-growing tech company transforming data for top UK brands.
- Benefits: Competitive salary, hybrid work model, and hands-on experience with AI.
- Other info: Perfect for early-career professionals eager to learn and grow.
- Why this job: Gain real-world exposure to AI and cloud delivery in a dynamic environment.
- Qualifications: 1+ years in data engineering, strong STEM background, and DevOps experience.
The predicted salary is between 36000 - 54000 € per year.
Salary: up to £45,000 per annum, depending on experience
Location: London, hybrid, in office Monday to Wednesday
Job ref: J13027
We are partnering with a fast growing tech company helping some of the best known UK brands turn first party data into real competitive advantage. This is not maintenance, this is building. You will ship data products, learn quickly, and help scale a platform that puts clean engineering at the heart of decision making. You will sit with talented AI engineers and analysts, learn how models are productionised at scale, and watch your pipelines power real outcomes.
What you will do:
- Build robust, well structured data pipelines in Python and SQL
- Work across cloud platforms, Azure, AWS, or GCP
- Integrate machine learning outputs into data products
- Automate and monitor flows so data moves securely and reliably
- Contribute to DevOps practices, CI and CD, testing and observability
What you will bring:
- 1 plus years in a data engineering or platform role
- Demonstrable experience with DevOps workflows
- An excellent STEM degree, Mathematics, Statistics, Computer Science, Engineering, or similar
- Curiosity, pragmatism, and a bias to ship
This is ideal for someone early in their data engineering journey who wants real exposure to AI, automation, and cloud delivery, not just theory, the real thing. If that sounds like you, let us talk. Be brave, make the move.
No sponsorship available, not available for post study visa holders.
Data Engineer, AI Customer Intelligence Engine, London, hybrid employer: Datatech Analytics
Join a dynamic and innovative tech company in London that prioritises employee growth and development, offering a collaborative work culture where you can build impactful data products alongside talented AI engineers. With a hybrid working model, you'll enjoy the flexibility of remote work while being part of a team that values clean engineering and real-world applications of data science. This role provides an excellent opportunity to enhance your skills in a fast-paced environment, making it an ideal choice for those eager to advance their careers in data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer, AI Customer Intelligence Engine, London, hybrid
✨Tip Number 1
Network like a pro! Reach out to people in the industry on LinkedIn or at local meetups. We can’t stress enough how important it is to make connections; 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 pipelines, projects, or any relevant work. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. We recommend practising coding challenges and discussing your past projects. Be ready to explain your thought process and how you tackle problems.
✨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 who are eager to dive into the world of data engineering.
We think you need these skills to ace Data Engineer, AI Customer Intelligence Engine, London, hybrid
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Python, SQL, and any cloud platforms like Azure or AWS. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our team. Don’t forget to mention your curiosity and eagerness to learn about AI and automation.
Showcase Your Projects:If you've worked on any relevant projects, make sure to include them in your application. Whether it's building data pipelines or integrating machine learning outputs, we love seeing practical examples of your work!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Datatech Analytics
✨Know Your Tech Stack
Make sure you’re familiar with the tools and technologies mentioned in the job description, like Python, SQL, and cloud platforms such as Azure, AWS, or GCP. Brush up on your knowledge of data pipelines and DevOps practices, as these will likely come up during the interview.
✨Showcase Your Projects
Prepare to discuss any relevant projects you've worked on, especially those involving data engineering or automation. Be ready to explain your role, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s data products, their approach to AI, and how they integrate machine learning outputs. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
✨Emphasise Your Curiosity
Since the role calls for curiosity and a bias to ship, be sure to highlight instances where you’ve taken initiative to learn something new or improve a process. Share examples that illustrate your eagerness to grow and adapt in a fast-paced environment.
