201 to 225 of 988 Kafka Jobs in the UK

teams having multiple levels of engineering. Strong experience in Java 17+, ideally with experience in using Spring Boot or Micronaut. Hands-on knowledge of Kafka, event-driven architecture, enterprise integration patterns and microservices. Solid understanding of payment systems and PSP integrations, including fraud, tokenisation, and settlement flows. Experience with More ❯

microservices purposed programming languages Runtimes: Experience in .NET Core, .Net based development Proficiency in Azure cloud services and frameworks Developing Event Driven Applications using Kafka, Zookeeper Knowledge of cloud-native CI/CD for change release Knowledge in Test Driven Development Azure Full stack developers need to be proficient More ❯

AppDynamics, ForgeRock, OAuth 2.0/SAML/OIDC, SPA, PWA, CMS, Akamai/Azure CDN. Languages: Angular, C, C#, Python, .NET, PowerShell. Integration skills: Kafka, Confluent, Event Hub, Pub/Sub, Messaging Platforms/MQs, RESTful APIs and Open API specifications, GraphQL, EDA, MQ, WebSocket, DataBricks. Data: SQLDB, MongoDB More ❯

Systems and Virtualisation (Windows and Linux). Infrastructure as Code and Operational Automation (e.g. Terraform, Ansible). Message Queueing and Streaming Fabrics (e.g. AMQP, Kafka, Kinesis). Docker and Kubernetes. Scripting (Shell and PowerShell). Basic Coding with a bias for Infrastructure (Python, Go, C#). IAM Policy and More ❯

experience on RESTful APIs - interconnected software components interaction, engineering and testing (e.g. NMS applications, controllers, orchestrators, supervisory systems, etc.). Experience and understanding of Kafka messaging bus. Experience in using monitoring tools like Nagios, Grafana, Prometheus and Kibana is desired. Deployment environment: Kubernetes, Docker, microservices. Experience on Talos Kubernetes More ❯

required but are highly desirable: Experience working with modern CI/CD tooling such as GitHub Actions or Azure DevOps Pipelines. Experience working with Kafka/Azure Service Bus/Event Grid. Exposure to Power Platform tools such as Power Automate and Power Apps. Exposure to data migration tools More ❯

required but are highly desirable: Experience working with modern CI/CD tooling such as GitHub Actions or Azure DevOps Pipelines. Experience working with Kafka/Azure Service Bus/Event Grid. Exposure to Power Platform tools such as Power Automate and Power Apps. Exposure to data migration tools More ❯

required but are highly desirable: Experience working with modern CI/CD tooling such as GitHub Actions or Azure DevOps Pipelines. Experience working with Kafka/Azure Service Bus/Event Grid. Exposure to Power Platform tools such as Power Automate and Power Apps. Exposure to data migration tools More ❯

Experience working in government, defence, or highly regulated industries with knowledge of relevant standards. Experience with additional data processing and ETL tools like Apache Kafka, Spark, or Hadoop. Familiarity with containerization and orchestration tools such as Docker and Kubernetes. Experience with monitoring and alerting tools such as Prometheus, Grafana More ❯

Python and SQL. Experience with big data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale ML inference pipelines into production environments. Proficiency with Docker for containerization and Kubernetes for More ❯

building, and deploying microservices (ideally with Java, Spring Boot, Node.js, or Python). Expertise designing and implementing event-driven systems using tools like Apache Kafka, RabbitMQ, Amazon EventBridge, Azure Event Grid, or Google Pub/Sub. Cloud Hyperscalers: Practical experience with AWS, Azure, and GCP. Leading iPaaS Tools: Proficiency More ❯

is desired but not essential. API development (FastAPI, Flask) Tech stack : Azure, Python, Databricks, Azure DevOps, ChatGPT, Groq, Cursor AI, JavaScript, SQL, Apache Spark, Kafka, Airflow, Azure ML, Docker, Kubernetes and many more. Role Overview: We are looking for someone who is as comfortable developing AI/ML models More ❯

is desired but not essential. API development (FastAPI, Flask) Tech stack : Azure, Python, Databricks, Azure DevOps, ChatGPT, Groq, Cursor AI, JavaScript, SQL, Apache Spark, Kafka, Airflow, Azure ML, Docker, Kubernetes and many more. Role Overview: We are looking for someone who is as comfortable developing AI/ML models More ❯

of building and managing real-time data pipelines across a track record of multiple initiatives. Expertise in developing data backbones using distributed streaming platforms (Kafka, Spark Streaming, Flink, etc.). Experience working with cloud platforms such as AWS, GCP, or Azure for real-time data ingestion and storage. Programming More ❯

solutions across various industries. Architectural Expertise: Strong expertise in designing and overseeing delivery of data streaming and event-driven architectures, with a focus on Kafka and Confluent platforms. In-depth knowledge in architecting and implementing data lakes and lakehouse platforms, including experience with Databricks and Unity Catalog. Proficiency in More ❯

JavaScript Experience in developing and deploying microservices architectures using Spring Boot, Spring Batch, Spring Data or similar frameworks Knowledge of JIRA, Junit and Apache Kafka are preferred Hands-on experience with NoSQL DB (CosmosDB, MongoDB) In-depth knowledge of REST API principles, protocol Familiarity with containerization tools and cloud More ❯

data repositories to support data-driven decision-making. Ingest data from a variety of sources, including on-premise SQL databases, REST APIs, and Apache Kafka streams. Apply data cleansing rules to ensure data meets quality and consistency standards. Model data appropriately for usage scenarios, including designing single-source-of More ❯

data repositories to support data-driven decision-making. Ingest data from a variety of sources, including on-premise SQL databases, REST APIs, and Apache Kafka streams. Apply data cleansing rules to ensure data meets quality and consistency standards. Model data appropriately for usage scenarios, including designing single-source-of More ❯

Experience with DevOps tools such as Docker, Kubernetes, Jenkins, etc. Innate curiosity about consumer behavior and technology Experience with event messaging frameworks like Apache Kafka A fan of movies and television is a strong plus. Required Education Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics More ❯

. - In-depth knowledge of data warehousing concepts and tools (e.G., Redshift, Snowflake, Google BigQuery). - Experience with big data platforms (e.G., Hadoop, Spark, Kafka). - Familiarity with cloud-based data platforms and services (e.G., AWS, Azure, Google Cloud). - Expertise in ETL tools and processes (e.G., Apache NiFi More ❯

. • In-depth knowledge of data warehousing concepts and tools (e.g., Redshift, Snowflake, Google BigQuery). • Experience with big data platforms (e.g., Hadoop, Spark, Kafka). • Familiarity with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud). • Expertise in ETL tools and processes (e.g., Apache NiFi More ❯

End: JavaScript, HTML, CSS, JSON, React.Js, TypeScript. Back-End: Java, Spring, Spring Boot, JPA/Spring Data. Databases: SQL and NoSQL. Message Queues: RabbitMQ, Kafka, Redis. Testing: JUnit, Mockito, JaCoCo. Tools & Platforms: Selenium, AWS, Azure, Linux, Git (BitBucket). Strong communication skills and a team-oriented mindset are essential. More ❯

End: JavaScript, HTML, CSS, JSON, React.Js, TypeScript. Back-End: Java, Spring, Spring Boot, JPA/Spring Data. Databases: SQL and NoSQL. Message Queues: RabbitMQ, Kafka, Redis. Testing: JUnit, Mockito, JaCoCo. Tools & Platforms: Selenium, AWS, Azure, Linux, Git (BitBucket). Strong communication skills and a team-oriented mindset are essential. More ❯

End: JavaScript, HTML, CSS, JSON, React.Js, TypeScript. Back-End: Java, Spring, Spring Boot, JPA/Spring Data. Databases: SQL and NoSQL. Message Queues: RabbitMQ, Kafka, Redis. Testing: JUnit, Mockito, JaCoCo. Tools & Platforms: Selenium, AWS, Azure, Linux, Git (BitBucket). Strong communication skills and a team-oriented mindset are essential. More ❯

skills An interest to learn the business supported by the applications Knowledge and desire to use agile software development practices Desirable Skills: JMS, MQ, Kafka MongoDB Knowledge of a range of common Open Source libraries used in Java development Database performance tuning (relational and document) Python/Shell scripting More ❯