Senior Data Engineer - (Python & SQL)

London
1 month ago
Applications closed

Senior Data Engineer (Python & SQL)
Location London with hybrid working Monday to Wednesday in the office
Salary £70,000 to £85,000 depending on experience
Reference J13026

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

What you will be doing
·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

What we are looking for
·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.
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 (url removed)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Data Engineering Jobs in the UK (2026 Guide)

Advertising data engineering jobs in the UK requires a different approach to most technical hiring. Data engineers occupy a distinct discipline that sits between software engineering, data science and cloud infrastructure — and the strongest candidates identify firmly with the data engineering community rather than with adjacent roles. General job boards consistently conflate data engineering with data analysis, data science and BI development, producing high application volumes but low candidate quality for specialist pipeline and platform roles. This guide, published by DataEngineeringJobs.co.uk, covers where to advertise data engineering roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Engineering Employers to Watch in 2026: UK and Global Companies Driving the Data Revolution

Data engineering is at the heart of the digital economy, transforming raw data into actionable insights, powering analytics, AI systems, and cloud infrastructure. As the UK and global markets continue to invest heavily in data platforms, pipelines, and real-time analytics, demand for skilled data engineers is growing rapidly. For professionals exploring opportunities on www.DataEngineeringJobs.co.uk , the critical question is: which companies are expanding, hiring, and shaping the future of data-driven business? This article highlights new data engineering employers to watch in 2026, including UK startups, scale-ups, and international firms expanding in the UK.

How Many Data Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.