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- Tasks: Build and own cloud-native data and ML pipelines from start to finish.
- Company: AI-first SaaS business focused on transforming data into insights.
- Benefits: Competitive salary, supportive culture, and clear career progression.
- Other info: Hybrid work model with a focus on wellbeing and work-life balance.
- Why this job: Join a team that values your voice and fosters your growth in AI.
- Qualifications: Strong Python/PySpark skills and experience with production systems.
The predicted salary is between 70000 - 80000 £ per year.
Location: London - Hybrid - Monday to Wednesday in office
Salary: £70,000 to £80,000 Dependent on Experience
We are working with an AI first SaaS business that transforms messy first party data into trusted, decision ready insight. They are scaling thoughtfully and building an engineering team where you will be heard, supported, and given real space to grow. If you enjoy building production grade data and ML pipelines, and want a culture that genuinely backs your development, this is worth exploring.
Responsibilities
- Building, shipping, and owning cloud-native data and ML pipelines end to end
- Strengthening CI/CD, deployments, monitoring, and platform reliability
- Partnering with product, engineering, and data science to deliver outcomes, not experiments
- Helping define the standards, patterns, and ways of working as the platform evolves
Qualifications
- Strong Python/PySpark and solid SQL coding experience
- Proven delivery of production systems at scale, not just prototypes
- Cloud experience and modern engineering practices, CI/CD, observability, automated testing
- Collaborative mindset, you share, ask, support, and raise the bar with the team
- Strong communicator, able to engage clearly with both technical and non-technical stakeholders
Why this team
- Supportive and inclusive culture where every voice is heard and respected
- Leadership that genuinely cares about representation and creating space for diverse careers in data
- Clear progression with options to grow into leadership, senior engineering, or deeper AI platform paths
- Strong mentoring, knowledge sharing, and a sensible approach to performance, wellbeing, and work life balance
Right to work in the United Kingdom is required. Sponsorship is not available. Apply to learn more or message for a confidential conversation.
Senior Data Engineer - ML and AI Platform Engineering in England employer: Datatech Analytics
Contact Detail:
Datatech Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer - ML and AI Platform Engineering in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We can’t stress enough how important it is to connect with people who are already in the game; they might just know about opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data and ML projects. We all love a good visual, so having something tangible to share during interviews can really set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Research the company and its culture, especially since this role values collaboration and communication. We recommend practising common interview questions and even some technical challenges to boost your confidence.
✨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’re always looking for passionate individuals who want to grow with us in the AI and data space.
We think you need these skills to ace Senior Data Engineer - ML and AI Platform Engineering in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your Python/PySpark and SQL expertise, and don’t forget to mention any cloud experience you have!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about building data and ML pipelines. Share specific examples of your past work and how it aligns with our mission at StudySmarter.
Showcase Your Collaborative Spirit: We love team players! In your application, mention instances where you've partnered with product, engineering, or data science teams. This will show us you’re ready to engage with both technical and non-technical stakeholders.
Apply Through Our Website: For the best chance of getting noticed, make sure to apply through our website. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Datatech Analytics
✨Know Your Tech Inside Out
Make sure you brush up on your Python, PySpark, and SQL skills. Be ready to discuss your experience with building data and ML pipelines, as well as any cloud technologies you've worked with. The more specific examples you can provide, the better!
✨Showcase Your Collaborative Spirit
This role values teamwork, so be prepared to share instances where you've partnered with product, engineering, or data science teams. Highlight how you’ve contributed to successful outcomes and how you support your colleagues in achieving their goals.
✨Demonstrate Your Problem-Solving Skills
Think of challenges you've faced in previous roles, especially around CI/CD, deployments, or platform reliability. Be ready to explain how you approached these issues and what solutions you implemented. This will show your ability to deliver production systems at scale.
✨Communicate Clearly and Confidently
As a Senior Data Engineer, you'll need to engage with both technical and non-technical stakeholders. Practice explaining complex concepts in simple terms, and be ready to answer questions about your thought process and decision-making.