National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Wolffsons | Junior Data Engineer (4 Days Per Week) – £37,500 – VISA Sponsorship Provided [in the UK] - Fully Remote (UK-based)

Wolffsons
Manchester
5 months ago
Applications closed

Job Title:Junior Data Engineer (4 Days Per Week) – £37,500 – VISA Sponsorship Provided [in the UK] - Fully Remote (UK-based)


About the Company:

We are hiring on behalf of a leading fintech company based in London, specializing in data-driven financial solutions. For over a decade, this company has been transforming the financial services industry by leveraging data analytics to offer personalized and flexible financial products. The company is now looking for a Junior Data Engineer to join their dynamic, fully remote team and help them continue their growth.


Key Responsibilities:

  • Assist in the design, development, and optimization of data pipelines to process large datasets.
  • Collaborate with data analysts and other teams to understand business requirements and deliver robust data engineering solutions.
  • Clean, preprocess, and validate data to ensure it is accurate and ready for analysis.
  • Work with cloud platforms, databases, and data warehouses to store and process data effectively.
  • Develop, maintain, and optimize ETL (Extract, Transform, Load) processes to integrate data from various sources.
  • Assist in monitoring and troubleshooting data systems to ensure smooth operation and performance.
  • Stay up-to-date with the latest trends and tools in data engineering, implementing best practices where applicable.


Skills & Qualifications:

  • Proficiency in programming languages such as Python, SQL, or other data-related languages.
  • Experience with cloud services (e.g., AWS, Google Cloud, Azure) and data storage solutions (e.g., Redshift, BigQuery).
  • Familiarity with data engineering tools and frameworks (e.g., Apache Spark, Kafka, Airflow).
  • Strong problem-solving skills and a passion for working with large datasets.
  • A degree in Computer Science, Data Engineering, Mathematics, or a related field (or equivalent experience).
  • Experience with data warehousing, database management, or similar engineering disciplines is a plus.


Benefits & Perks:

  • Salary: £37,500 per annum.
  • Visa Sponsorship available for international candidates.
  • Fully remote working within the UK, with one office visit per month in London for team collaboration.
  • Four-day workweek to promote a healthy work-life balance.
  • Free lunch provided during office visits.
  • 32 days paid annual leave, including bank holidays.
  • Performance-related bonuses to reward individual contributions.
  • Opportunity to work in an innovative, data-driven fintech company and grow within the industry.


How to Apply:

Submit your CV and be part of an exciting opportunity to advance your career with a leading fintech company.


National AI Awards 2025

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.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.