Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer

Hyper Recruitment Solutions
North Yorkshire
2 weeks ago
Create job alert

Join to apply for the Data Engineer role at Hyper Recruitment Solutions

Role Overview

We are currently looking for a Data Engineer to join a leading Life Science company based in the East Yorkshire area. As the Data Engineer, you will be responsible for designing, developing, and maintaining robust data integration solutions.

Key Duties And Responsibilities

Your duties as the Data Engineer will be varied; however, the key duties and responsibilities are as follows:

  • Extract, transform, and load (ETL) data from numerous data sources (from ERP to cloud-based systems).
  • Automate processes using appropriate scripting and integration tools.
  • Ensure data quality, integrity, and consistency throughout the projects.
  • Work closely with business users, IT teams, and project stakeholders to understand data structures and needs.

Role Requirements

To be successful in your application to this exciting role as the Data Engineer, we are looking to identify the following on your profile and past history:

  • Relevant degree in a related field.
  • Proven industry experience in data engineering projects and data warehousing.
  • Experience with Talend, Snowflake, and ETL tools.

We are an Equal Opportunities Employer and welcome applications from all qualified candidates.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.