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- Tasks: Design and deliver cloud-based data and machine learning pipelines using Python and SQL.
- Company: Join an AI-first SaaS business with a supportive and inclusive culture.
- Benefits: Competitive salary, hybrid working, and opportunities for skill development.
- Why this job: Make a real impact by working with cutting-edge data technologies in a collaborative environment.
- Qualifications: Experience in Python, SQL, and modern cloud data platforms required.
- Other info: Great career progression and a chance to contribute to meaningful projects.
The predicted salary is between 65000 - 80000 £ per year.
Location | London with hybrid working Monday to Wednesday in the office
Salary | £65,000 to £80,000 depending on experience
We are partnering with an AI first SaaS business that turns complex first party data into trusted, decision ready insight at scale. You will join a collaborative data and engineering team building a modern, cloud agnostic data and AI platforms. This role is well suited to an experienced data engineer who enjoys working thoughtfully with real world data, contributing to reliable production systems, and developing clear and well-structured Python and SQL.
Why join:
- Supportive and inclusive culture where people are encouraged to contribute and be heard
- Clear progression with space to develop your skills at a sustainable pace
- An environment where collaboration, learning, and thoughtful engineering are genuinely valued
What you will be doing:
- Contributing to the design and delivery of cloud-based data and machine learning pipelines
- Working with Python, PySpark and SQL to build clear and maintainable data transformations
- Helping shape scalable data models that support analytics, machine learning, and product features
- Collaborating closely with Product, Engineering, and Data Science teams to deliver meaningful production outcomes
What we are looking for:
- Experience using Python for data transformation, ideally alongside PySpark
- Confidence working with SQL and production data models
- Experience working with at least one modern cloud data platform such as GCP, AWS, Azure, Snowflake, or Databricks
- Experience contributing to data pipelines that run reliably in production environments
- A collaborative mindset with clear and thoughtful communication
Right to work in the UK is required. Sponsorship is not available now or in the future.
Apply to learn more and see if this could be the next step for you. If you have a friend or colleague who may be interested, referrals are welcome. For each successful placement, you will be eligible for our general gift or voucher scheme.
Datatech is one of the UK's leading recruitment agencies specialising in analytics and is the host of the critically acclaimed Women in Data event. For more information, visit www.datatech.org.uk
Senior Data Engineer - (ML and AI Platform) 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)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, and cloud platforms. This gives you a chance to demonstrate your expertise and makes you stand out during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding data pipelines. Practice common interview questions related to data engineering and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace Senior Data Engineer - (ML and AI Platform)
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 experience with Python, SQL, and any cloud platforms you've worked with. We want to see how you can contribute to our collaborative team!
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 aligns with our mission at StudySmarter. Keep it concise but engaging – we love a good story!
Showcase Your Projects: If you've worked on relevant projects, don’t hesitate to mention them! Whether it's a personal project or something from your previous job, we want to see how you've applied your skills in real-world scenarios. It helps us understand your thought process and problem-solving abilities.
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’re considered for the role. Plus, it gives you a chance to explore more about our culture and values!
How to prepare for a job interview at Datatech Analytics
✨Know Your Tech Stack
Make sure you’re well-versed in Python, PySpark, and SQL. Brush up on your experience with cloud platforms like GCP, AWS, or Azure. Be ready to discuss specific projects where you’ve used these technologies to solve real-world problems.
✨Showcase Your Collaboration Skills
This role values teamwork, so be prepared to share examples of how you've worked closely with Product, Engineering, and Data Science teams. Highlight instances where your communication made a difference in project outcomes.
✨Prepare for Technical Questions
Expect questions about data pipelines and production environments. Think through scenarios where you’ve contributed to reliable systems and be ready to explain your thought process and the impact of your work.
✨Ask Insightful Questions
At the end of the interview, ask questions that show your interest in the company’s culture and future projects. Inquire about their approach to machine learning and how they foster collaboration within teams.
