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

Apply Now

Data Engineer - Hybrid/Bristol - Up to £55k

Bristol
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer - Hybrid/Bristol - Up to £55,000

Job Title: Data Engineer

Location: Hybrid/Bristol (Min. 2 days per week)

Remuneration: £45,000 - £55,000 per annum

Responsibilities:

  • Pipeline Development and Optimisation: Continuously assess and improve the performance of data enrichment pipelines, ensuring their efficiency, dependability, and scalability.

  • Data Management: Design and implement robust processes for data ingestion and cleaning, supporting machine learning and analytical models.

  • Collaborative Problem-Solving: Work closely with data scientists to troubleshoot, identify, and resolve complex issues, ensuring smooth operations across the board.

  • Model Development and Deployment: Assist in building, training, monitoring, and deploying cutting-edge machine learning models.

  • Stay Current with AI/ML Trends: Keep up to date with the latest advancements in data processing, AI, and ML, and incorporate them into our client's processes to improve efficiency.

  • Adaptable Approach: Collaborate across different functions as required, including taking on backend development tasks like API creation with support from more senior engineers.

    Our client, a leading player in the risk industry, is seeking a skilled and motivated Data Engineer to join their innovative team in Bristol. With a minimum requirement of two days per week in the office, this position offers the opportunity to contribute to the development and optimisation of AI/ML-powered data enrichment workflows and infrastructure. We are seeking someone with a strong Python expertise, a creative mindset, and a passion for working with modern AI/ML systems.

    To succeed in this role, you should have a Bachelor's degree (or equivalent) in computer science, mathematics, or a related field, along with at least three years of relevant experience. You should have a proven ability to design, build, and deploy machine learning models and/or data pipelines, and be proficient in Python with hands-on experience in PySpark or Pandas.

    In addition to technical expertise, we value strong analytical skills, the ability to address data quality issues and optimise model performance, and the willingness to think creatively and independently to solve complex problems. Experience in deploying and managing machine learning models in production environments, knowledge of advanced techniques such as gradient boosting and large-scale text embedding models, and familiarity with tools such as Databricks, Git, CI/CD pipelines, and software testing methodologies are also preferred qualifications.

    If you are ready to join a dynamic and innovative team, apply now and take the next step in your career as a Data Engineer!

    Please note that only successful applicants will be contacted.

    Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you.

    KEYWORDS:

    Python / Data pipelines / Data enrichment / PySpark / Pandas / Machine learning / AI/ML / Model deployment / Data cleaning / Data ingestion / Databricks / Git / CI/CD pipelines / API development / Gradient boosting / Text embedding models / Production ML / Software engineering / Data processing / Analytical models / Data science / Model monitoring / Testing / Deployment techniques / Python / Data pipelines / Data enrichment / PySpark / Pandas / Machine learning / AI/ML / Model deployment / Data cleaning / Data ingestion / Databricks / Git / CI/CD pipelines / API development / Gradient boosting / Text embedding models / Production ML / Software engineering / Data processing / Analytical models / Data science / Model monitoring / Testing / Deployment techniques / Python / Data pipelines / Data enrichment / PySpark / Pandas / Machine learning / AI/ML / Model deployment / Data cleaning / Data ingestion / Databricks / Git / CI/CD pipelines / API development / Gradient boosting / Text embedding models / Production ML / Software engineering / Data processing / Analytical models / Data science / Model monitoring / Testing / Deployment techniques

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.

The Best Free Tools & Platforms to Practise Machine Learning Skills in 2025/26

Machine learning (ML) has become one of the most in-demand career paths in technology. From predicting customer behaviour in retail to detecting fraud in banking and enabling medical breakthroughs in healthcare, ML is transforming industries across the UK and beyond. But here’s the truth: employers don’t just want candidates who have read about machine learning in textbooks. They want evidence that you can actually build, train, and deploy models. That means practising with real tools, working with real datasets, and solving real problems. The good news is that you don’t need to pay for expensive software or courses to get started. A wide range of free, open-source tools and platforms allow you to learn machine learning skills hands-on. Whether you’re a beginner or preparing for advanced roles, you can practise everything from simple linear regression to deploying deep learning models — at no cost. In this guide, we’ll explore the best free tools and platforms to practise machine learning skills in 2025, and how to use them effectively to build a portfolio that UK employers will notice.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.