Data Engineer

Digital Waffle
Tamworth
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

BI Engineer (Azure, Python, SQL)

Location: Birmingham (4 days a week on-site)
Salary: £45k - £48k

Opportunity

A fantastic opportunity has come up to work for a genuine market leader in an exciting and innovative industry. They plan to build a newly created BI and Data Engineering division to work alongside other Data and Analytics teams across the group.

For this role, they need someone to serve as a central resource from within their Strategy and Analytics department, also working with, but not exclusive to, the Commercial, Finance, and Operational business functions, to help advance the group’s data infrastructure and support in transforming data into actionable insights and triggered events for Business Intelligence (BI) and Customer Relationship Management (CRM) system purposes.

This role will be instrumental in leveraging data to ensure a fully integrated approach to data-driven decision-making and also business strategy.

Day-to-day tasks

Work across the group and with the divisions' data partners to leverage all available data, building out the group's database, reporting and insights capabilities to enable data-led decision making.
Design, develop and maintain scalable, user-friendly and automated systems, data solutions and reporting that will support our analytical and business needs.
Support the insight team with visualisations, reporting and stakeholder engagement through monthly/quarterly/annual departmental reviews.
Use data science/statistical modelling tools in collaboration with the analyst team and departmental stakeholders to develop Artificial Intelligence (AI) and Machine Learning (ML) functions and analytics.
Create and manage a knowledge-base, including documentation of your designs (e.g., system design, functional design, data flow design) ensuring there is version control and contingency processes for all aspects.

Required skills and experience for the role

Demonstrable experience or certification(s) within the field of data engineering, data science, and/or business analysis.
Practical experience of database design and data transformation, supported by ETL processing.
Managing data pipelines & orchestration that enable the transfer and processing of data (Databricks, Microsoft Fabric, Alteryx, Snowflake, Apache).
Coding and programming, capable of working through complex problems with others from the team, adapting quickly to changing market trends and business needs (SQL, Python or R).
Utilising cloud-based services and corresponding toolsets (Microsoft Azure, GCP, AWS or similar).
Comfortable handling structured and unstructured data, from 1st, 2nd, and 3rd party data sources, combining multiple data sets to produce a cohesive picture of performance and derive insights and recommendations.
Experience working directly with business stakeholders ensuring complex information is articulated in a meaningful way.

Applying for the opportunity

If you feel you have the required skills and experience and want to be considered for this opportunity, please forward an up-to-date version of your CV. If we feel your profile is a suitable match, someone will contact you within 48 hours.
#J-18808-Ljbffr

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.