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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 gift voucher scheme.
- Why this job: Make a real impact on data foundations that power innovative AI solutions.
- Qualifications: Strong experience in Python, SQL, and cloud environments.
- Other info: Join a supportive team and mentor fellow engineers while growing your career.
The predicted salary is between 60000 - 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. 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 (AWS, 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 (AWS, SQL, Python) in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with AWS, SQL, or Python. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines and real-world data transformation. This will give potential employers a taste of what you can do and how you tackle messy data.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering challenges. Be ready to discuss how you've handled incomplete or inconsistent data in the past. We want to see your problem-solving skills in action!
✨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 are proactive about their job search.
We think you need these skills to ace Senior Data Engineer (AWS, SQL, Python) in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and data pipelines. We want to see how you've tackled messy data and built robust systems, so don’t hold back on those details!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how you’ve contributed to AI-driven products. Let us know why you’re excited about this role and our company.
Showcase Your Projects: If you’ve worked on any relevant projects, be sure to mention them! Whether it’s a personal project or something from your previous job, we love seeing real-world applications of your skills.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Datatech Analytics
✨Know Your Tech Stack
Make sure you’re well-versed in Python, SQL, and the cloud technologies mentioned in the job description. Brush up on your experience with AWS, GCP, or Azure, and be ready to discuss how you've used these tools to build and maintain data pipelines.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled messy, real-world data in the past. Think about specific challenges you faced and how you transformed incomplete or inconsistent data into reliable datasets. This will demonstrate your hands-on experience and ability to think critically.
✨Emphasise Collaboration
Since this role involves mentoring and supporting other engineers, be ready to talk about your experiences working in a team. Share instances where you’ve conducted code reviews or provided technical guidance, highlighting your collaborative spirit and leadership skills.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data processes and the challenges they face. This shows your genuine interest in the role and helps you understand how you can contribute to their goals. Plus, it gives you a chance to assess if the company culture aligns with your values.