1 to 25 of 163 Apache Jobs in the UK excluding London

Strong programming and integration skills: Java, JUNIT, REST services, DQL, SQL, GWT Proficiency in XML, XSD, xDB, XSL Operating systems: Linux and Windows Web and directory services: Apache HTTPD, Tomcat, Apache DS DevOps tools: Git, Jenkins, SonarQube, Bitbucket, Octopus More ❯

Strong programming and integration skills: Java, JUNIT, REST services, DQL, SQL, GWT Proficiency in XML, XSD, xDB, XSL Operating systems: Linux and Windows Web and directory services: Apache HTTPD, Tomcat, Apache DS DevOps tools: Git, Jenkins, SonarQube, Bitbucket, Octopus More ❯

/MS in Computer Science, Software Engineering, or equivalent technical discipline. 8+ years of hands-on experience building large-scale distributed data pipelines and architectures. Expert-level knowledge in Apache Spark, PySpark, and Databricks—including experience with Delta Lake, Unity Catalog, MLflow, and Databricks Workflows. Deep proficiency in Python and SQL, with proven experience building modular, testable, reusable pipeline More ❯

/MS in Computer Science, Software Engineering, or equivalent technical discipline. 8+ years of hands-on experience building large-scale distributed data pipelines and architectures. Expert-level knowledge in Apache Spark, PySpark, and Databricks—including experience with Delta Lake, Unity Catalog, MLflow, and Databricks Workflows. Deep proficiency in Python and SQL, with proven experience building modular, testable, reusable pipeline More ❯

customer data Continuously improve existing systems, introducing new technologies and methodologies that enhance efficiency, scalability, and cost optimisation Essential Skills for the Senior Data Engineer: Proficient with Databricks and Apache Spark, including performance tuning and advanced concepts such as Delta Lake and streaming Strong programming skills in Python with experience in software engineering principles, version control, unit testing and More ❯

data quality, or other areas directly relevant to data engineering responsibilities and tasks Proven project experience developing and maintaining data warehouses in big data solutions (Snowflake) Expert knowledge in Apache technologies such as Kafka, Airflow, and Spark to build scalable and efficient data pipelines Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data More ❯

in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages such as Python, Java, and SQL. Strong knowledge of data warehousing, data lakes, and data lakehouse architectures. Excellent analytical and More ❯

in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages such as Python, Java, and SQL. Strong knowledge of data warehousing, data lakes, and data lakehouse architectures. Excellent analytical and More ❯

of SQL and Python You have strong hands-on experience of building scalable data pipelines in cloud based environments using tools such as DBT, AWS Glue, AWS Lake Formation, Apache Spark and Amazon Redshift You have a good knowledge of data modelling, ELT design patterns, data governance and security best practices You're collaborative and pragmatic with great communication More ❯

of SQL and Python You have strong hands-on experience of building scalable data pipelines in cloud based environments using tools such as DBT, AWS Glue, AWS Lake Formation, Apache Spark and Amazon Redshift You have a good knowledge of data modelling, ELT design patterns, data governance and security best practices You're collaborative and pragmatic with great communication More ❯

of SQL and Python You have strong hands-on experience of building scalable data pipelines in cloud based environments using tools such as DBT, AWS Glue, AWS Lake Formation, Apache Spark and Amazon Redshift You have a good knowledge of data modelling, ELT design patterns, data governance and security best practices You're collaborative and pragmatic with great communication More ❯

of SQL and Python You have strong hands-on experience of building scalable data pipelines in cloud based environments using tools such as DBT, AWS Glue, AWS Lake Formation, Apache Spark and Amazon Redshift You have a good knowledge of data modelling, ELT design patterns, data governance and security best practices You're collaborative and pragmatic with great communication More ❯

Science (or similar) from a good University highly desirable. Nice to Have: Familiarity with message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Understanding of infrastructure and DevOps (Terraform, Ansible, AWS, Kubernetes). Exposure to More ❯

Science (or similar) from a good University highly desirable. Nice to Have: Familiarity with message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Understanding of infrastructure and DevOps (Terraform, Ansible, AWS, Kubernetes). Exposure to More ❯

indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

frameworks, and clear documentation within your pipelines Experience in the following areas is not essential but would be beneficial: Data Orchestration Tools: Familiarity with modern workflow management tools like Apache Airflow, Prefect, or Dagster Modern Data Transformation: Experience with dbt (Data Build Tool) for managing the transformation layer of the data warehouse BI Tool Familiarity : An understanding of how More ❯

field. Technical Skills Required • Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). • Experience with Apache Spark or any other distributed data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or More ❯

field. Technical Skills Required • Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). • Experience with Apache Spark or any other distributed data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or More ❯

field. Technical Skills Required • Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). • Experience with Apache Spark or any other distributed data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or More ❯

field. Technical Skills Required • Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). • Experience with Apache Spark or any other distributed data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines and More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines and More ❯