Data Engineer

Wolfspeed

Belfast, Northern Ireland

7 months ago

Applications closed

Related Jobs

View all jobs

Data Engineer

Sanderson Cardiff, Cymru / Wales, CF10 2AF, United Kingdom

£60,000 – £72,000 pa Hybrid

Data Engineer

Saffron housing Norwich, United Kingdom

£56,000 pa On-site

Data Engineer

Harnham - Data & Analytics Recruitment London, United Kingdom

£70,000 – £90,000 pa Hybrid

Data Engineer

Harnham - Data & Analytics Recruitment Manchester, United Kingdom

£70,000 – £90,000 pa Hybrid

Data Engineer

Sanderson Bristol, United Kingdom

£45,000 – £48,000 pa Permanent

Data Engineer

Vermelo RPO Salford, United Kingdom

£40,000 – £60,000 pa Remote

Posted: 14 Oct 2025 (7 months ago)

Save job

Create job alert

Applications closed

The Role

As part of a global team you will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data solutions and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists while ensuring optimal data delivery architecture is consistent throughout ongoing projects. The Data Engineer will be responsible for the day-to-day activities related to the implementation of new services and support for existing services.

We are looking for intelligent, driven individuals who are passionate about what they do and have exceptional teamwork skills. The skills and experience needed for this role are listed below. However, we understand that there might be a few requirements that you don't meet or skills that you don't yet have. That's ok! If you are a smart, passionate, hardworking individual who is eager to learn we would like to speak with you about joining our wolf pack!

Your day-to-day - We do what others say can't be done

Provide technical expertise and execute the design, development and support of data solutions for Wolfspeed business partners, including configuration, administration, monitoring, performance tuning, debugging, and operationalization.
Build and maintain data solutions using Snowflake, dbt (data build tool), Fivetran, Azure Cloud (storage, VMs, containers, Azure Data Factory), Python, Docker and SQL.
Participate in the development lifecycle using Agile / DevOps methodologies using Azure DevOps.
Translate simple to complex requirements into functional and actionable tasks.
Serve as a subject matter expert for Wolfspeed operations for data integration from enterprise applications (SAP, Oracle, ModelN, Salesorce, Workday, etc.), using that knowledge to craft data solutions that provide maximum visibility to global stakeholders.

Your Profile - Ready to join the Pack?

Minimum 3+ years' experience in a Data Engineering role, or Software Engineering role with a focus on data.
Hands-on skills with a programming language such as Python, Java, Go, etc.
Public cloud experience (Azure, AWS or GCP)
Writing complex SQL Queries
ETL tools (Fivetran, Azure Data Factory) or writing custom data extraction applications, Data Modeling, Data Warehousing and working with large-scale datasets.
Experience leveraging DevOps and lean development principles such as Continuous Integration, Continuous Delivery/Deployment using tools like Azure DevOps, Github, Gitlab, etc.
Designing and building modern data pipelines and data streams
This role may require additional duties and/or assignments as designated by management.

#J-18808-Ljbffr

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

Industry Insights

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

Apr 9, 2026

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.

Mar 24, 2026

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.

Feb 11, 2026

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.