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

Nominate & Attend

Data Engineer

The Green Recruitment Company
Worcester
4 days ago
Create job alert

The Green Recruitment Company is working with an Environmental and Sustainability Business that supports and empower their customers journey to net zero. To join their Data-Technology team, we have an opportunity for a Data Engineer to help support the wider business (cross-functional) to meet their reporting and data requirements.


About the role:

  • The Data Engineer will be working with the latest innovative technologies, to design, build and maintain data solutions, constructing process to surface data both internally for reporting purposes and externally through the customer portal.
  • The Data Engineer will be responsible for developing scalable data pipelines to integrate diverse data sources whilst ensuring data quality under the framework of a new Data Platform for real time application integration and reporting, and will work closely with business stakeholders to support data-driven decision making by delivering clean, well-structured datasets that can be utlised for reporting purpose in a performent, secure way.


Key responsibilities:

  • Taking full ownership of assigned projects and BAU tasks.
  • Maintaining current pipelines within Azure ADF and Synapse Analytics.
  • Build a process of transforming raw data from various CRM system into a harmonised and curated layer.
  • Develop the usage of event driven topics for usage of various subscribers.
  • Investigate and document Architectural Spikes to help foster best practice within the Data Team.
  • Developing and creating data science tools to give a deeper understanding of the customer book.
  • Recording and updating of work on Project Management System (Azure DevOps).
  • Own and enhance the BAU runbook for engineering operations
  • Develop the instrumentation and monitoring of IT automated tasks
  • Taking a lead in the engineering function of the data team


Requirements:

Qualifications:Bachelor’s degree or above in Computing or Software Development or similar


Experience required:

  • 3-5 years' Cloud-based Data Engineering experience,
  • Previous experience of formal methodologies with data engineering
  • Experience leading or working in an engineering team or function
  • Previous experience of using the Azure Stack
  • Experience working in a proactive analytics function
  • Experience of working in the Utilities sector
  • Experience leading technical projects


Skills & Technologies required:

  • Proficiency in cloud-based data engineering tools (ADF, Synapse Analytics, S3, Lamda)
  • Proficiency in using PySpark notebooks for ELT.
  • Fostering and cultivating a culture of best practices
  • Strong analytical and problem-solving skills.
  • Ability to work independently and as part of a functional and cross-functional team
  • Excellent communication and documentation skills.
  • Proven ability to design, evaluate and score engineering options
  • Formal data engineering qualification


On offer:Salary £42 000 - £45 000 (depending on experience) with an attractive company benefit package & career development

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.

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.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.