6 of 6 Permanent Distributed Computing Jobs in the North of England

with expertise in Databricks, Hadoop/Spark. Strong programming skills in Python, Scala, or SQL, with knowledge of CI/CD platforms. Proficiency with distributed computing frameworks and cloud platforms (AWS, Azure, Google Cloud). Familiarity with data modeling, database systems, and SQL optimisation. Excellent problem-solving, communication More ❯

on testing frameworks, best practices, and automation strategies. Job Requirements Your profile: 4+ years of experience as a QA Automation Specialist. Proven experience in distributed computing (e.g., Spark) and software development. Strong background in database testing, preferably with PostgreSQL. Solid understanding of object-oriented programming and core development More ❯

of network and operating system support experience 3+ years of technical support experience 3+ years of information security and compliance experience 4+ years of distributed systems experience - Knowledge of distributed computing environments - Knowledge of security best practices - Experience with network troubleshooting tools (telnet, test-netconnection, tracert, tracetcp More ❯

Engineering (SRE), including monitoring, alerting, and incident management. Hands-on experience with Kafka, MuleSoft, and Oracle DB. Familiarity with performance tuning, system design, and distributed computing concepts. Experience with CI/CD pipelines and infrastructure-as-code (e.g., Jenkins, Terraform, Ansible) is a plus. Ability to lead and More ❯

. Strong background in designing and building end-to-end data pipelines. Proficient in Python and/or Scala; solid understanding of SQL and distributed computing principles. Experience with Delta Lake, Lakehouse architecture, and data governance frameworks. Excellent client-facing and communication skills. Experience in Azure Data Services More ❯

data pipeline designs and supports the development of data pipelines to support model development. Proficient with software tools that develop data pipelines in a distributed computing environment (PySpark, GlueETL). Supports integration of model pipelines in a production environment. Develops understanding of SDLC for model production. Reviews pipeline More ❯