Senior Data Engineer

twentyAI
London, England
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Certain Advantage South Bank

Senior Data Engineer

Hays Technology Abingdon

Senior Data Engineer

CBSbutler Holdings Limited trading as CBSbutler Reading

Senior Data Engineer

83zero London

Senior Data Engineer

Pontoon Warwick

Senior Data Engineer

Fraser & Co. Talent Partners Limited Clerkenwell
Posted
5 Jun 2025 (11 months ago)
Share
Save job
Create job alert

Senior Data Engineer – Snowflake Platform Build Location: London (2 days a week on site) Contract: 6 month sign on (18–24 month project) Interview process : 2 stages twentyAI's customer is building a next version of their data platform, with Snowflake at the core.

Interested in learning more about this job Scroll down and find out what skills, experience and educational qualifications are needed.

The PoC is in place — now they need someone who’s been through this before to lead the implementation and help scale the platform across the business.

The project involves migrating our current on-prem Data Lake to Snowflake, while keeping storage on a private cloud.

You’ll be setting the foundations: building out ETL pipelines, establishing best practices, and working closely with teams across trading, finance, compliance, and ops.

Profile: Strong experience implementing Snowflake in a lead or senior capacity Solid background in Python, PySpark, and Spark Hands-on with platform setup – ideally with a DevOps-first approach Exposure to AWS environments Experience working with data from trading platforms or within commodities, banking, or financial services Tech environment: Primary Platform: Snowflake Other Tech: DBT, Databricks, Spark, PySpark, Python Cloud: AWS (preferred), Private Cloud storage Data Sources: Financial/trading systems

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.

Products

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning 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.

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.