Contract Data Engineer

Footasylum
Rochdale
8 months ago
Applications closed

Related Jobs

View all jobs

Contract Data Engineer (Azure) - Agile IT Team

Data Engineer (Banking Experience)

Data Engineer - HealthTech

Urgent | Contract Senior Data Engineer - Azure + Databricks + Snowflake

AWS Data Engineer (contract)

Data Engineer - AWS | London Insurance

Description

We are looking for a contract Data Engineer, to join us as we look to support our stakeholders with Finance, specifically improving the accuracy of our existing finance reporting.

You will deliver data products in line with business requirements which enable data driven decision making. Understand business needs, design and deliver cloud solutions which enable data analysis across the business.



You'll help is to be ready to move our platform to the next stage and explore Data Engineering concepts, demonstrating what a well designed data platform can provide for our customers.





  • Design, deliver and improve data products in a timely fashion.
  • Develop the current data warehouse solution, designing and developing facts and dimensions for use in analysis and financial decision making.
  • Assist the BI and Analytics teams in interpreting requirements and deliver engineering solutions which meet the business needs.
  • Find and implement new methods or technology to reduce the time required to ingest and self-serve data.

The Team

The data team is an enabling team and as such it is important to note that we are a key function for all other teams across the business. We consist of two teams – Business Intelligence Developers and Data Engineering – who work closely alongside each other from end to end. We design solutions together and share best practice. Within the teams we recognise individual skillsets and encourage knowledge sharing sessions and self-development.

About You


  • Experience with finance/financial systems and concepts
  • Azure Databricks
  • Azure Data Factory
  • Excellent SQL skills
  • Good Python/Spark/pyspark skills
  • Experience of Kimball Methodology and star schemas (dimensional model).
  • Experience of working with enterprise data warehouse solutions.
  • Experience of working with structured and unstructured data
  • Experience of a retail environment preferred
  • A good understanding of cloud technologies and DevOps practice - Scaling and cost, CI/CD, cost saving best practice.
  • Open to collaborative working


Diversity



We recognise and value the importance of diversity to help make sure we have lots of different perspectives when we are building products and services. We know that this will help us build useful and accessible things which our customers will love. This is great news for our business. Diversity for us is also, importantly, about building happy teams full of people that want to learn and want to be inspired by each other and our different experiences and backgrounds.



Recruitment Process

We’ll help make the interview process as transparent and stress-free as possible.

We review applications individually, and if we feel you would be a good fit, we’ll invite you for a call or Teams video for an informal chat about the role and to see if we’re a good fit for you.

We value open and honest conversations and collaboration, allowing you to learn about our work in an informal and friendly environment. We want to know about you and why you feel this is your opportunity.

Please note this is not a remote role, and we expect that you will be able to attend Head Office in a hybrid way in Greater Manchester.

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 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.

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.

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.