Data Engineer (Spark, Kafka)

Windsor
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

We are partnered with a leading global consultancy that is searching for a contractor with the following skillset to work on a LONG-TERM contract within the ENERGY sector:

Role: Data Engineer (Spark, Kafka)

Location: Windsor

Style: Hybrid

Rate: up to £500 per day (inside IR35)

Duration: 6 months (initially – view to extend)

Key responsibilities:

  • Design, implement, and manage Kafka-based data pipelines and messaging solutions to support critical business operations and enable real-time data processing.

  • Configure, deploy, and maintain Kafka clusters, ensuring high availability and scalability to maximize uptime and support business growth.

  • Monitor Kafka performance and troubleshoot issues to minimize downtime and ensure uninterrupted data flow, enhancing decision-making and operational efficiency.

  • Collaborate with development teams to integrate Kafka into applications and services.

  • Develop and maintain Kafka connectors such as JDBC, MongoDB, and S3 connectors, along with topics and schemas, to streamline data ingestion from databases,

  • NoSQL data stores, and cloud storage, enabling faster data insights.

  • Implement security measures to protect Kafka clusters and data streams, safeguarding sensitive information and maintaining regulatory compliance

    Key Skills:

  • Design, build, and maintain reliable, scalable data pipelines. Data Integration, Data Security and Compliance

  • Monitor and manage the performance of data systems and troubleshoot issues.

  • Strong knowledge of data engineering tools and technologies (e.g. SQL, ETL, data warehousing), Experience in tools like Azure ADF, Apache Kafka, Apache Spark SQL, Proficiency in programming languages such as Python, PySpark

  • Good written and verbal communication skill

  • Experience in managing business stakeholders for requirement clarification

    If you are interested and have the relevant experience, please apply promptly and we will contact you to discuss it further.

    Yilmaz Moore

    Senior Delivery Consultant

    London | Bristol | Amsterdam

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.

Careers

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.

Jobs

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.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 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.