Data Engineer

Yeovil
2 days ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer required by our market leading, award winning, professional services organisation based in Yeovil.
The successful Data Engineer, you'll play a vital role in designing, building, and maintaining sophisticated data pipelines and ensuring the integrity of our clients extensive customer data. Your work will support data-driven decision-making across the business, helping to drive forward key customer insights and analytics.
In this role, you will work closely with cross-functional teams to deliver high-quality data infrastructure that powers marketing efforts and analytics. Reporting directly into the Head of Data, you will collaborate with a team of experienced data professionals while continuing to develop your expertise in data engineering.
Key Responsibilities

  • Design & Build Data Pipelines: Create and maintain scalable data pipeline architecture that supports business needs.
  • Data Management: Assemble large, complex data sets to meet business and technical requirements.
  • Process Improvement: Identify and implement process enhancements, automate manual tasks, and optimize data delivery.
  • Data Integration: Build ETL infrastructure to ensure smooth data extraction, transformation, and loading.
  • Collaboration: Work alongside stakeholders, including data scientists and analysts, to meet data infrastructure needs.
  • Data Quality: Ensure data is clean, accurate, and readily available for reporting and analysis.
  • GDPR Compliance: Maintain data in line with GDPR obligations and support the implementation of retention policies.
  • Documentation & Data Governance: Produce clear documentation to enable efficient data governance and management.
  • Customer Data Management: Manage the "golden record" of customer data, ensuring accurate entity matching and a single customer view.
  • API & Microservices: Build and manage APIs and microservices with a focus on scalable architectures.
    Required Skills & Experience
  • Experience: 3-5 years of hands-on experience with big data tools and frameworks.
  • Technical Skills: Proficiency in SQL, Python, and data pipeline tools such as Apache Kafka, Apache Spark, or AWS Glue.
  • Problem-Solving: Strong analytical skills with the ability to troubleshoot and resolve data issues.
  • Communication: Excellent communication skills for collaborating with technical and non-technical teams.
  • Data Visualization: Experience with tools like Tableau or Power BI.
  • Power BI Skills: Knowledge of DAX, M, and Power Query for data tables and ingestion.
  • Data Structures: Familiarity with XML and JSON data formats.
    Apply today and make an impact with your data engineering expertise!
    This fantastic role comes with a competitive basic salary, an annual bonus, share plans, discounted merchandise, healthcare, gym discount, pension, long service awards, life cover and enhanced family leave to name but a few

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

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

Jobs

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.