Kafka Architect Job in Buckinghamshire

Salt
Buckinghamshire
9 months ago
Applications closed

Related Jobs

View all jobs

Solutions Architect

Technical Architect

Senior Solutions Architect

Data Engineer

Principal Data Engineer

(Senior) Lead Data Engineer

Salt are partnered with one of the worlds leading Technology consultancies who require aKafka Architectto join one of their end clients teams on a12-month rolling contract. The role isINSIDE IR35and requires3-days a week on-site in Milton Keynes.

Job Title: Kafka Architect

Job Overview:

A Kafka Architect is responsible for designing, implementing, and managing Apache Kafka infrastructure and data pipelines. This role involves collaboration with various teams to understand business requirements and create scalable, efficient, and robust Kafka-based solutions to handle real-time data streaming needs. The Kafka Architect ensures the high availability, security, and performance of the Kafka ecosystem, providing technical leadership and guidance to developers and operations teams.

Key Responsibilities:

Design and Architecture:Develop and implement the architecture for Apache Kafka infrastructure to meet business and technical requirements.Design data pipelines and streaming applications using Kafka and associated technologies.Create and maintain documentation of the Kafka architecture, including data flow diagrams, architecture diagrams, and operational procedures.Implementation and Deployment:Set up and configure Kafka clusters, topics, producers, consumers, and connectors.Ensure secure, high-availability, and fault-tolerant Kafka environments.Implement best practices for data retention, partitioning, replication, and monitoring.Monitoring and Optimization:Monitor Kafka clusters’ performance and troubleshoot issues related to scalability, latency, and throughput.Optimize Kafka configurations for better performance and resource utilization.Implement monitoring and alerting systems for Kafka health and performance using tools like Prometheus, Grafana, or equivalent.Collaboration and Support:Work closely with data engineers, developers, and IT operations to integrate Kafka with other systems and applications.Provide technical support and guidance to development teams on Kafka-related issues.Conduct training sessions and workshops to upskill teams on Kafka usage and best practices.Innovation and Improvement:Stay updated with the latest developments in Kafka and related technologies.Evaluate and recommend new tools, technologies, and processes to improve the Kafka ecosystem.Lead proof-of-concept projects to test new solutions and approaches.

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

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Jobs Careers

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Jobs

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

🍪 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.