6 of 6 Distributed Computing Jobs in Manchester

multiple programming languages such as Python, C++. Java. Extensive experience with data processing tools and platforms such as Kafka, Flink, Databricks. Skilled in managing distributed computing management systems, like SLURM, LSF. Knowledgeable in both relational and non-relational databases (e.g., SQL, MongoDB). Familiarity with cloud platforms (AWS More ❯

multiple programming languages such as Python, C++. Java. Extensive experience with data processing tools and platforms such as Kafka, Flink, Databricks. Skilled in managing distributed computing management systems, like SLURM, LSF. Knowledgeable in both relational and non-relational databases (e.g., SQL, MongoDB). Familiarity with cloud platforms (AWS More ❯

multiple programming languages such as Python, C++. Java. Extensive experience with data processing tools and platforms such as Kafka, Flink, Databricks. Skilled in managing distributed computing management systems, like SLURM, LSF. Knowledgeable in both relational and non-relational databases (e.g., SQL, MongoDB). Familiarity with cloud platforms (AWS More ❯

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 ❯

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 ❯