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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 a gift voucher scheme.
- Why this job: Make a real impact on AI products while mentoring fellow engineers.
- Qualifications: Strong experience in Python, SQL, and cloud environments.
- Other info: Join a supportive team focused on quality and long-term success.
The predicted salary is between 60000 - 75000 £ 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. Alongside the hands on work, you will mentor and support other data engineers through code reviews, shared problem solving, and thoughtful technical guidance.
- 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
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.
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.
Senior Data Engineer SQL Python 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 SQL Python in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with online communities. 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 and SQL. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering challenges. Be ready to discuss how you've tackled messy data and built robust pipelines. Practice makes perfect, so consider mock interviews with friends or mentors.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be just right for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Senior Data Engineer SQL Python 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 passion for data 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 candidates who can think critically about data quality and edge cases, so share those experiences with us!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother 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 dealt with messy, real-world data. Highlight how you transformed and validated this data to create reliable datasets. This will demonstrate your ability to handle the challenges that come with the role.
✨Emphasise Collaboration
Since this position involves mentoring other engineers, be ready to share examples of how you've supported your team in the past. Discuss your approach to code reviews and collaborative problem-solving, showcasing your commitment to a supportive engineering culture.
✨Think Long-Term
The company values long-term thinking, so be prepared to discuss how you ensure the reliability and scalability of data pipelines. Talk about your experience taking ownership of systems from design through to long-term support, and how you plan for future growth.