At a Glance
- Tasks: Build and maintain data pipelines using SQL and Python for AI-powered products.
- Company: Join an innovative AI-first SaaS business in London.
- Benefits: Competitive salary, hybrid work model, and excellent learning opportunities.
- Other info: Collaborative team environment with exposure to modern cloud technologies.
- Why this job: Work on cutting-edge AI solutions that impact real customers.
- Qualifications: Experience in data engineering, strong SQL and Python skills required.
The predicted salary is between 45000 - 50000 £ per year.
We are looking for a Data Engineer to join an AI-first SaaS business developing next-generation analytics and decision intelligence products.
Working alongside Product Managers, AI Engineers and Analysts, you will help build the data platforms, pipelines and models that power production AI solutions used by organisations across multiple sectors.
What You'll Be Doing
- Building and maintaining data pipelines using SQL and Python
- Developing data models for analytics and AI applications
- Working with cloud platforms including Azure, AWS or GCP
- Supporting CI/CD processes and automated deployments
- Implementing data quality, monitoring and validation processes
- Collaborating with Product, Engineering and AI teams on new product development
What We're Looking For
- Commercial Data Engineering experience
- Strong SQL skills
- Python experience
- Exposure to Azure, AWS or GCP
- Understanding of data modelling and data warehousing principles
- Experience working with Git and CI/CD processes
- Strong communication skills and a collaborative mindset
Nice to Have
- SaaS or product development experience
- Exposure to AI or machine learning environments
- Experience with Databricks, Fabric or modern cloud data platforms
The Opportunity
- Work on AI-powered products rather than internal reporting
- Join a collaborative product engineering team
- Exposure to modern cloud and AI technologies
- Opportunity to influence products used by real customers
- Excellent environment for learning and development
For more information make an application today!
Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes!
Data Engineer in London employer: Datatech Analytics
Join a forward-thinking AI-first SaaS company in London, where you will be part of a dynamic team dedicated to developing cutting-edge analytics and decision intelligence products. With a strong emphasis on collaboration, employee growth, and exposure to modern cloud technologies, this role offers an excellent environment for learning and development, alongside competitive benefits and a hybrid work model that promotes work-life balance.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in data engineering. Building relationships can lead to job opportunities that aren’t even advertised.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving SQL and Python. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Ace the Interview
Prepare for technical interviews by practicing common data engineering problems and questions. Don’t forget to brush up on your cloud platform knowledge too! We recommend doing mock interviews with friends or using online resources to get comfortable.
✨Apply Through Our Website
When you find a role that excites you, 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 join our team!
We think you need these skills to ace Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your SQL and Python skills, and any experience with cloud platforms like Azure or AWS. We want to see how your background aligns with what we're looking for!
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 AI-first SaaS business. Keep it engaging and relevant to the role.
Showcase Your Projects:If you've worked on any relevant projects, make sure to mention them! Whether it's building data pipelines or working with CI/CD processes, we love to see practical examples of your skills in action.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at Datatech Analytics
✨Know Your SQL Inside Out
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss your experience with SQL in detail, and maybe even solve a few problems on the spot. Practising common SQL queries and understanding how to optimise them can really set you apart.
✨Show Off Your Python Skills
Since Python is a key part of the role, be ready to talk about your projects and how you've used Python in data engineering. If you can, bring examples of your work or even code snippets that demonstrate your proficiency. This will show your practical experience and problem-solving abilities.
✨Familiarise Yourself with Cloud Platforms
The job mentions Azure, AWS, or GCP, so make sure you have a good grasp of at least one of these platforms. Understand their data services and how they integrate with data pipelines. Being able to discuss your experience with cloud technologies will definitely impress the interviewers.
✨Emphasise Collaboration and Communication
This role involves working closely with various teams, so highlight your collaborative mindset. Prepare examples of how you've successfully worked in teams, especially in cross-functional settings. Good communication skills are essential, so be ready to demonstrate how you can convey complex ideas clearly.
