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For Companies At a Glance
- Tasks: Build and own cloud-native data and ML pipelines while collaborating with diverse teams.
- Company: AI-first SaaS business focused on transforming data into insights.
- Benefits: Competitive salary, supportive culture, clear progression, and strong mentoring.
- Why this job: Join a team that values your voice and supports your growth in AI and data.
- Qualifications: Strong Python/PySpark, SQL experience, and a collaborative mindset.
- Other info: Hybrid work model with a focus on wellbeing and work-life balance.
The predicted salary is between 70000 - 80000 ÂŁ per year.
We are working with an AI first SaaS business that transforms messy first party data into trusted, decisionâready 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 productionâgrade data and ML pipelines, and want a culture that genuinely backs your development, this is worth exploring.
What you'll be doing
- Building, shipping, and owning cloudânative 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
What you'll bring
- 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 â you share, ask, support, and raise the bar with the team
- Strong communicator, able to engage clearly with both technical and nonâtechnical 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 workâlife balance
No sponsorship or postâstudy visas.
Senior Data Engineer - ML and AI Platform Engineering in London employer: Datatech Analytics
Contact Detail:
Datatech Analytics Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Senior Data Engineer - ML and AI Platform Engineering in London
â¨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your data and ML projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
â¨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the companyâs products. Be ready to discuss how your experience aligns with their needs, especially around cloud-native data pipelines.
â¨Tip Number 4
Donât forget to apply through our website! Itâs the best way to ensure your application gets seen. Plus, we love hearing from candidates who are genuinely excited about joining our team.
We think you need these skills to ace Senior Data Engineer - ML and AI Platform Engineering in London
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV speaks directly to the role of Senior Data Engineer. Highlight your experience with Python, PySpark, and SQL, and donât forget to mention any cloud experience you have. We want to see how your skills align with what weâre looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why youâre passionate about building data and ML pipelines. Share specific examples of your past work that demonstrate your collaborative mindset and ability to deliver production systems at scale.
Showcase Your Communication Skills: As a Senior Data Engineer, youâll need to engage with both technical and non-technical stakeholders. Make sure your application reflects your strong communication skills. We love candidates who can explain complex concepts in simple terms!
Apply Through Our Website: We encourage you to apply through our website for the best chance of being noticed. Itâs super easy, and youâll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Datatech Analytics
â¨Know Your Tech Inside Out
Make sure you brush up on your Python, PySpark, and SQL skills. Be ready to discuss specific projects where you've built production-grade data and ML pipelines. The more you can demonstrate your technical expertise, the better you'll connect with the interviewers.
â¨Showcase Your Collaborative Spirit
This role values a collaborative mindset, so be prepared to share examples of how you've worked with product, engineering, and data science teams. Highlight instances where your communication skills helped bridge gaps between technical and non-technical stakeholders.
â¨Understand CI/CD and Cloud Practices
Familiarise yourself with modern engineering practices, especially around CI/CD, observability, and automated testing. Be ready to discuss how you've implemented these in past roles and how they contributed to platform reliability.
â¨Emphasise Growth and Learning
The company is keen on supporting your development, so express your enthusiasm for learning and growing within the role. Share your career aspirations and how you see yourself evolving in the field of AI and data engineering.
