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- Tasks: Shape messy data into reliable datasets for AI-driven products.
- Company: Fast-growing AI-driven SaaS platform with a collaborative culture.
- Benefits: Competitive salary, hybrid working, and opportunities for mentorship.
- Why this job: Make a real impact on innovative AI products while mentoring fellow engineers.
- Qualifications: Strong experience in Python, SQL, and cloud environments.
- Other info: Join a supportive team that values diverse perspectives and long-term thinking.
The predicted salary is between 70000 - 85000 £ per year.
Location: London with hybrid working Monday to Wednesday in the office
Salary: £70,000 to £85,000 depending on experience
We are working with a fast growing AI driven SaaS Platform Company where data underpins intelligent products used at scale. Large volumes of first party data flow through the platform and are shaped into trusted inputs for analytics, product features, and machine learning.
They are looking for a Senior Data Engineer to take ownership of the core data pipelines that make this platform work in practice. This role is about working with real world data that directly feeds AI driven products. Data arrives incomplete, inconsistent, and sometimes ambiguous. Your role is to shape it into clear, reliable, decision ready datasets that product, analytics, and machine learning teams can confidently rely on.
Python and SQL are fundamental to the work. You will design and maintain transformation logic, think carefully about data quality and edge cases, and ensure downstream behaviour remains reliable as data volumes and AI capabilities grow. The work sits within a modern cloud data stack. You will work with technologies such as AWS, GCP or Azure, distributed processing frameworks like Spark, and modern data stores and warehouses such as Snowflake or BigQuery. The emphasis is on building robust, well structured data logic that scales alongside the platform.
You will be part of a collaborative and supportive engineering team where quality, clarity, and long term thinking are valued. Different perspectives are encouraged, and engineers are trusted to contribute in their own way. Alongside the hands on work, you will mentor and support other data engineers through code reviews, shared problem solving, and thoughtful technical guidance.
What we are looking for:
- Strong, hands on experience using Python and SQL in production environments
- Experience building and maintaining data pipelines using technologies such as Spark, Snowflake, BigQuery, or similar
- Experience working in cloud environments such as AWS, GCP or Azure, with an understanding of data processing at scale
- Confidence working with messy, real world data and improving it through careful transformation and validation
- A track record of taking ownership of important systems and seeing work through from design to long term support
- A collaborative approach with experience mentoring and supporting other engineers through code review, shared problem solving, and knowledge sharing
If this role aligns with your experience using Python and SQL and you enjoy building the data foundations that power AI driven products while supporting other engineers to do their best work, we would like to hear from you.
Right to work in the UK is required. Sponsorship is not available now or in the future.
Apply to find out more!
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 - Python and SQL in City of London employer: Datatech Analytics
Contact Detail:
Datatech Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer - Python and SQL in City of 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. You never know who might have a lead on your dream job!
✨Show Off Your Skills
Don’t just tell them you’re great at Python and SQL—show it! Work on personal projects or contribute to open-source. Share your work on platforms like GitHub to demonstrate your expertise and passion for data engineering.
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and understanding data pipelines. Practice common interview questions and be ready to discuss how you've tackled real-world data challenges in the past.
✨Apply Through Us!
We’ve got your back! Apply for the Senior Data Engineer role directly through our website. It’s the best way to ensure your application gets the attention it deserves, and we’re here to support you every step of the way!
We think you need these skills to ace Senior Data Engineer - Python and SQL in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and SQL, as well as any relevant cloud technologies like AWS or GCP. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for this Senior Data Engineer role. Share specific examples of how you've tackled messy data and built robust pipelines. Let your personality shine through!
Showcase Your Problem-Solving Skills: In your application, highlight instances where you've taken ownership of data systems and improved them. We love seeing how you approach challenges, so share your thought process and the impact of your work.
Apply Through Our Website: We encourage you to apply directly 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 important updates from us!
How to prepare for a job interview at Datatech Analytics
✨Know Your Tech Stack
Make sure you’re well-versed in Python and SQL, as these are fundamental to the role. Brush up on your experience with cloud environments like AWS, GCP, or Azure, and be ready to discuss how you've used technologies like Spark, Snowflake, or BigQuery in your previous projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific instances where you've tackled messy, real-world data. Highlight your approach to transforming and validating this data, and how you ensured it was reliable for downstream teams. Real examples will make your experience stand out!
✨Emphasise Collaboration
This role values teamwork, so be ready to share experiences where you’ve mentored other engineers or contributed to code reviews. Discuss how you’ve supported your team in problem-solving and knowledge sharing, as this shows you’re a great fit for their collaborative culture.
✨Think Long-Term
Demonstrate your understanding of building robust data pipelines that can scale. Talk about your experience taking ownership of systems from design to long-term support, and how you ensure quality and clarity in your work. This will show that you’re not just focused on immediate tasks but also on sustainable solutions.
