Data Engineer

Insight
London, England
6 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Relation Therapeutics London, United Kingdom
Permanent

Data Engineer, Strategic Account Services

Amazon London, United Kingdom
Permanent

Data Engineer - Security Products, Monitored Access

Amazon London, United Kingdom
£40,000 – £60,000 pa On-site

Senior Data Engineer

Synthesia London, United Kingdom
Hybrid

Senior Research Engineer - Data

Synthesia London, United Kingdom
Remote

Senior Simulation Data Engineer

PhysicsX London, United Kingdom
Posted
6 Nov 2025 (6 months ago)
Share
Save job
Create job alert

Insight Global’s client is looking for a Senior Data Engineer to join their Finance and Operations team, responsible for designing and maintaining Azure-based data pipelines and APIs, building and optimizing ETL processes, managing large datasets, troubleshooting data issues, and documenting technical solutions. The ideal candidate will have strong coding skills in Python and SQL, experience with dbt, Azure DevOps, and CI/CD best practices, and a solid understanding of data warehousing principles. Success in this role requires excellent communication, a collaborative mindset, and proactive problem-solving to mitigate blockers and deliver scalable solutions. Candidates with experience in tools like Snowflake, Airflow, or Terraform, familiarity with infrastructure as code, and exposure to financial and operational data domains will stand out. This is a full-time onsite position in our London office, working closely with global teams to ensure data quality, automation, and continuous improvement.


Please note, this is a 6 month contract-to-hire position and would require you to be on-site 5 days a week out of the London office.


Day to Day:

  • Develop and maintain Azure-based data pipelines for Finance and Operations.
  • Build and optimize ETL workflows using SQL and dbt.
  • Write Python scripts for data transformation and automation.
  • Deploy infrastructure as code and manage cloud data solutions.
  • Collaborate with project managers and contractors across global teams.
  • Ensure data quality and compliance with best practices.
  • Troubleshoot and resolve data-related issues promptly.
  • Document technical solutions and maintain test scripts.


Must Haves:

  • Strong experience in data engineering.
  • Expertise in Azure (cloud platform)
  • SQL (advanced ETL and query optimization)
  • dbt (data transformation pipelines)
  • Python (data transformation and automation scripts)
  • Azure DevOps / GitHub (CI/CD pipelines, source control)
  • Data warehousing and ETL best practices


Plusses:

  • Experience with similar tools or technologies (e.g., Snowflake, Airflow, Terraform)
  • Familiarity with infrastructure as code
  • Ability to participate in architectural decisions
  • Strong problem-solving and continuous improvement mindset

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.