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- Tasks: Design and build data pipelines using Python and SQL for impactful AI projects.
- Company: Join a leading AI-first SaaS business with a collaborative culture.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Why this job: Make a real difference by transforming data into trusted insights.
- Qualifications: Strong experience in Python and SQL, with a focus on data quality.
- Other info: Mentorship opportunities and a supportive environment for career development.
The predicted salary is between 60000 - 72000 £ per year.
An AI first SaaS business that transforms high quality first party data into trusted, decision ready insight at scale is looking for a Senior Data Engineer to join its growing data and engineering team. This role sits at the core of data engineering. You will work with data that is often imperfect and transform it into well structured, reliable datasets that other teams can depend on. The focus is on engineering high quality data foundations rather than analytics or cloud infrastructure alone.
You will design and build clear, maintainable data pipelines using Python and SQL within a modern data and AI platform, with a strong focus on data quality, robustness, and long term reliability. You will also play an important mentoring role within the team, supporting and guiding other data engineers and helping to raise engineering standards through thoughtful, hands on leadership.
Why join- A supportive and inclusive environment where different perspectives are welcomed and people are encouraged to contribute and be heard
- Clear progression with space to deepen your technical expertise and grow your confidence at a sustainable pace
- A team that values collaboration, good communication, and shared ownership over hero culture
- The opportunity to work on meaningful data engineering problems where quality genuinely matters
- Designing and building cloud based data and machine learning pipelines that prepare data for analytics, AI, and product use
- Writing clear, well-structured Python, PySpark, and SQL to transform and validate data from multiple upstream sources
- Taking ownership of data quality, consistency, and reliability across the pipeline lifecycle
- Shaping scalable data models that support a wide range of downstream use cases
- Working closely with Product, Engineering, and Data Science teams to understand data needs and constraints
- Mentoring and supporting other data engineers, sharing knowledge and encouraging good engineering practices
- Contributing to the long term health of the data platform through thoughtful design and continuous improvement
- Strong experience using Python and SQL to transform large, real world datasets in production environments
- A deep understanding of data structures, data quality challenges, and how to design reliable transformation logic
- Experience working with modern data platforms such as Azure, GCP, AWS, Databricks, Snowflake, or similar
- Confidence working with imperfect data and making it fit for consumption downstream
- Experience supporting or mentoring other engineers through code reviews, pairing, or informal guidance
- Clear, thoughtful communication and a collaborative mindset
You do not need to meet every requirement listed. What matters most is strong, hands on experience using Python and SQL to work confidently with complex, real world data, apply sound engineering judgement, and help others grow through your experience.
Right to work in the UK is required. Sponsorship is not available now or in the future.
Apply to find out more about the role. 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.
Senior Data Engineer - (Python & SQL) in 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 & SQL) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work at companies you're interested in. A friendly chat can lead to insider info and even referrals that could get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best Python and SQL projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really impress potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering challenges. Be ready to discuss how you've tackled imperfect data and built reliable pipelines. We want to hear about your hands-on experience!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Data Engineer - (Python & SQL) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and SQL, especially in transforming large datasets. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
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 you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Problem-Solving Skills: In your application, mention specific challenges you've faced with data quality and how you tackled them. We appreciate candidates who can think critically and adapt to imperfect data situations.
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 updates from us!
How to prepare for a job interview at Datatech Analytics
✨Know Your Data Inside Out
Before the interview, brush up on your experience with Python and SQL. Be ready to discuss specific projects where you transformed large datasets, focusing on the challenges you faced and how you overcame them. This will show your hands-on experience and confidence in dealing with real-world data.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled data quality issues in the past. Think of examples where you designed reliable transformation logic or improved data pipelines. Highlighting your ability to work with imperfect data will demonstrate your fit for the role.
✨Emphasise Collaboration and Mentorship
Since this role involves mentoring other engineers, be ready to share your experiences in guiding team members. Discuss any code reviews or pair programming sessions you've led, and how you fostered a collaborative environment. This will showcase your leadership skills and commitment to raising engineering standards.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data challenges and their engineering practices. This not only shows your genuine interest in the role but also gives you a chance to assess if the company culture aligns with your values, especially regarding collaboration and shared ownership.
