11 of 11 Remote/Hybrid Distributed Computing Jobs in the UK excluding London

team. Component Design: Design scalable application components, microservices, and data integration layers to support high-throughput regulatory reporting. Big Data Processing: Develop and optimize distributed data processing jobs using Apache Spark, Hadoop, and Hive to aggregate and transform large-scale financial datasets. Real-Time Streaming: Build and maintain real … experience building microservices and RESTful APIs using Spring Boot , Spring Cloud, Spring Data, and Spring Security. Big Data Technologies: Strong, hands-on experience with distributed computing frameworks, specifically Apache Spark , Hadoop , and Hive . Proven ability to write and optimize complex Spark jobs. Real-Time Streaming: Practical experience ...

processing solutions using Python and PySpark.* Write complex and high-performing SQL queries for data extraction, transformation, and analysis.* Work with large datasets and distributed computing frameworks to support data engineering initiatives.* Collaborate with architects, analysts, and business stakeholders to deliver data-driven solutions.* Troubleshoot and resolve performance ...

team technical initiatives and influence organisational direction through technical authority. Evaluate and integrate emerging approaches including generative AI, Agentic AI, advanced optimisation, and scientific computing into scalable solutions. Supply to and shape internal ML platforms, reusable frameworks, and shared scientific computing capabilities. Mentor senior engineers and data scientists … prototyping, productionizing, and scaling complex ML systems in production environments. Deep and demonstrable expertise in machine learning algorithms, statistical modelling, optimisation techniques, and scientific computing with a consistent record of applying these to deliver production-grade products. Strong software engineering and system design expertise, including distributed systems, scalable ...

world’s most innovative companies, delivering extraordinary electronic products from chips to boards to systems for the most dynamic market applications including consumer, hyperscale computing, 5G communications, automotive, aerospace industrial and health. At Cadence, we hire and develop leaders and innovators who want to make an impact … motorsport, electric vehicle, and renewable energy companies worldwide. As a Lead Software Engineer, you will work at the intersection of mathematical modelling, high-performance computing, and software engineering to create advanced simulation solutions for complex multi-physics systems. You will help design cutting-edge numerical solvers, GPU-accelerated computing ...

software engineering best practices: testing, design patterns, CI/CD, Git. Experience building ETL/ELT or streaming data pipelines. Exposure to microservices and distributed system concepts. Experience working with cloud platforms, ideally AWS, but Azure/GCP also acceptable. Understanding of distributed compute, large-scale data systems ...

transform diverse data sources into valuable insights for our client’s National Security customers. You will collaborate with clients to solve complex challenges, utilising distributed computing techniques to handle large-scale, real-time, and unstructured data. Responsibilities include: Design and develop data pipelines, including ingestion, orchestration ...

transform diverse data sources into valuable insights for our client's National Security customers. You will collaborate with clients to solve complex challenges, utilising distributed computing techniques to handle large-scale, real-time, and unstructured data. Responsibilities include: Design and develop data pipelines, including ingestion, orchestration ...

scaling KDB+ solutions. Strong knowledge of market data, trading systems, or real-time analytics. Experience with data pipelines, cloud-based KDB+ deployments, and distributed computing. Ability to lead projects, optimize system architecture, and mentor junior developers. Preferred Qualifications (for all levels): Experience with high-frequency trading, quantitative finance ...

related technical discipline. Extensive experience as a Software Engineer, with required proficiency in Python, including proven success in implementing and deploying robust, scalable distributed systems in production. Demonstrated experience designing, managing, and orchestrating complex systems involving scalable data infrastructure, hardware interfaces, and machine learning models. Expertise in defining … design, architecture decisions, and software engineering practices to multi-disciplinary teams. Desirable Skills, Qualifications & Experience: Experience leveraging Kubernetes for application deployment, and familiarity with distributed computing frameworks (e.g., Ray, Spark), or specialised batch schedulers/resource managers (e.g., Slurm, Volcano, Kueue). Demonstratedexpertisewith specialised serving engines (e.g.,vLLM ...

platform technologies to drive continuous improvement and innovation. Technical Expertise Recognised expert in Data Architecture, Data Modelling, Engineering, and data platform design. Experience utilising distributed and non‐distributed compute architectures with strong proficiency in Python, SQL, Spark, and Scala. Experience architecting CI/CD frameworks (Azure DevOps, GitHub ...

depth commercial experience in the following key areas: Databricks – Lakehouse architecture, Spark, Delta Lake, workflows and performance tuning. Apache Spark & Scala – High-performance distributed data processing and optimisation. Cloud Data Engineering (AWS) – Cloud-native data platforms and distributed computing. Data Services Architecture & Engineering – Distributed processing, reprocessing, streaming ...