Junior Data Engineer

Willis Towers Watson
Ipswich
5 months ago
Applications closed

Related Jobs

View all jobs

Junior Data Engineer - Data Pipelines, SQL & ML Ops

Junior Data Engineer: Data Mesh & Cloud Platform

Junior Data Engineer

Junior Data Engineer: Cloud Data Pipelines & AI

Junior Data Engineer - Modelling & Simulation (Defense)

Junior Data Engineer - Data Mesh & Cloud Platform

Description

Who We Are Looking For:

Are you passionate about solving complex data challenges and developing innovative cloud-based data solutions? Do you enjoy applying logical thinking to technical problems, and take satisfaction in seeing your solutions make a tangible impact?

We are seeking a Junior Data Engineer who is eager to learn, grow, and contribute to the way we move, store, and process data within our Corporate Risk and Broking (CRB) business. Whether you have experience with cloud platforms such as Azure, Google Cloud, or AWS, or you’re just starting out, what matters most is your curiosity, motivation, and willingness to learn.

If you’re someone who thrives in a fast-paced, collaborative environment, and you’re keen to develop your skills in modern data engineering practices, we’d love to hear from you.

The Role:

  • Designing, building, and optimizing data pipelines using Azure Synapse, Azure Data Factory, and Azure Fabric.
  • Writing and fine-tuning PySpark notebooks to handle massive data workloads efficiently.
  • Troubleshooting and enhancing ETL/ELT workflows in Azure Synapse.
  • Managing and organizing Data Lakes to ensure seamless data access and performance.
  • Integrating AI/LLM models into data pipelines to drive innovation and insights.
  • Collaborating with Data Scientists, AI Engineers, Data Analysts, and Business domain experts to create powerful data-driven solutions.
  • Participating and assisting with data security, governance, and compliance within our Azure ecosystem.
  • Staying ahead of the curve with emerging cloud, AI, and big data technologies.
Qualifications

The Requirements:

  • 1+ years of experience in Data Engineering, with competency in Cloud Data Tools.
  • Solid programming skills in a language like C# or Python.
  • Understanding of data warehousing, modeling, and basic data architecture either through experience or education
  • Strong problem-solving skills and a knack for debugging tricky data issues.
  • Excitement of working with data and the business outcomes from data.
  • Massive curiosity of how things work and are built.
  • Great communication skills and a team-player attitude.

Bonus Points If You Have

  • Certifications in Azure Data Engineer Associate or Azure Solutions Architect.
  • Experience with real-time streaming solutions like Azure Stream Analytics, Kafka, or Event Hubs.
  • Familiarity with Databricks and its integration with Azure Synapse.
  • Knowledge of Graph Databases and NoSQL technologies.
  • Knowledge of AI/LALM applications and how they connect with data pipelines
  • Experience with CI/CD pipelines, DevOps, and Infrastructure as Code (IaC).

Why You’ll Love Working Here

  • Work with the latest cloud and AI technologies, always stay ahead of the game.
  • Mentoring and coaching through your journey will be all around you due to the many team members you will interact with
  • Be part of a collaborative and forward-thinking team that values your ideas.
  • Competitive salary, benefits, and plenty of opportunities to grow your career.
  • A flexible, modern work environment designed for how people work today.

We’re not just looking for someone to check off the skills list, we want a problem solver, an innovator, and someone who loves working with data.

At WTW, we believe difference makes us stronger. We want our workforce to reflect the different and varied markets we operate in and to build a culture of inclusivity that makes colleagues feel welcome, valued and empowered to bring their whole selves to work every day. We are an equal opportunity employer committed to fostering an inclusive work environment throughout our organisation. We embrace all types of diversity.


#J-18808-Ljbffr

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.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.