401 to 425 of 971 Kafka Jobs

distributed systems and cloud-native architectures, with experience shaping technical direction across teams and stakeholders Solid expertise in relevant technologies such as AWS, Terraform, Kafka/MSK, Airflow, Glue or Spark, and building scalable data solutions Experience with modern data ecosystems including data lakes/lakehouse architectures, Iceberg ...

engineering techniques Have an understanding of Java IOC frameworks such as Spring or Guice Understand next generation messaging and streaming technologies such as Kafka, Solace or Ignite Preferred Qualifications, Capabilities, and Skills: Values the very best technologists and promotes the technical career path within financial services in a flat ...

security data strategy aligned with business and regulatory requirements Qualifications Strong experience with Elastic Stack and data engineering technologies such as Logstash, Beats, Kafka or similar Expertise in Elastic data modelling, indexing and performance optimisation Experience designing scalable log collection and processing architectures Knowledge of data governance, retention ...

complex. Always looking forward to creating a bigger impact for our colleagues and customers.A bonus if you haveExperience with Terraform, Kubernetes and AWSExperience with Kafka or any other messaging-oriented middlewareExperience with reactive programmingExposure to the Payments industry domain especially Cards and other payment schemes)Exposure to PCI-DSSAbout ...

lock-free programming, hardware-aware optimization, or FPGA-adjacent systems. Experience with ML/data tooling such as PyTorch, JAX, CUDA, GPU clusters, Ray, Kafka, Kubernetes, Spark, or comparable technologies. Understanding of market microstructure, backtesting pitfalls, transaction costs, and the operational needs of live quantitative strategies. Experience in environments ...

Expertise Deep Kubernetes experience (EKS/GKE/AKS; operators/CRDs a bonus). Terraform (multi-cloud). GitOps tooling: Flux or ArgoCD. Kafka/event streaming. Distributed SQL databases. Language: Go, Rust, or similar (AI-accelerated development welcome). Cloud & Reliability Prometheus, Grafana, and OpenTelemetry observability stack ...

distributed systems and cloud-native architectures, with experience shaping technical direction across teams and stakeholders Solid expertise in relevant technologies such as AWS, Terraform, Kafka/MSK, Airflow, Glue or Spark, and building scalable data solutions Experience with modern data ecosystems including data lakes/lakehouse architectures, Iceberg ...

theorem aren’t just theory here—they’re part of our daily engineering conversations. Our stack includes Java, Vert.x, RxJava, Groovy, Couchbase, and Kafka , built using Terraform , running in Kubernetes on Azure utilising GitHub Actions pipelines. We follow Agile principles, adapting Kanban and other methodologies to fit the team ...

Excellent interpersonal skills and a collaborative spirit Desired: Experience in React (ReactJS). Experience in Event Driven Programming including experience with RabbitMQ, Kafka or other message brokers. Experience and/or knowledge of .Net/C# or any OOPS Concepts and technologies. Experience working with CI/CD processes ...

distributed systems and cloud-native architectures, with experience shaping technical direction across teams and stakeholders Solid expertise in relevant technologies such as AWS, Terraform, Kafka/MSK, Airflow, Glue or Spark, and building scalable data solutions Experience with modern data ecosystems including data lakes/lakehouse architectures, Iceberg ...

dedicated time for your personal development What you'll be working with: Backend: Distributed, event-driven core Java (90% of the code-base), MySQL, Kafka Frontend: Javascript, Vue.js Deployment: Kubernetes, Nomad Data analytics: Python & Jupyter notebooks, Parquet, Docker Testing: JUnit, JMH, JCStress, Jenkins, Selenium, many in-house tools... ...

dedicated time for your personal development What you’ll be working with: •Backend: Distributed, event-driven core Java (90% of the code-base), MySQL, Kafka •Frontend: Javascript, Vue.js •Deployment: Kubernetes, Nomad •Data analytics: Python & Jupyter notebooks, Parquet, Docker •Testing: JUnit, JMH, JCStress, Jenkins, Selenium, many in-house tools... ...

Java, with strong experience in Big Data technologies such as Spark, Hadoop etc. Practical knowledge of building real-time event streaming pipelines (e.g., Kafka, Spark Streaming, Kinesis). Proficiency in AWS cloud environments. Proven experience developing modern data architectures including Data Lakehouse and Data Warehousing. A solid understanding ...

including experience contributing to scoping, estimation and proposal developmentNice to haveSnowflake ecosystem experience with tools such as dbt, Airflow/Dagster, Matillion/Fivetran, Kafka/Kinesis/Event Hubs or similarExperience with Snowflake capabilities such as Snowpark, Streams & Tasks, Dynamic Tables, Data Sharing or Iceberg tables, CoCo, CoWork ...

committed to providing our team members with the support and resources they need to succeed. Java and/or Rust, AWS, FIX protocol, Kafka , Kubernetes and Cloud (AWS or Azure). What We’re Looking For 8+ years of professional software engineering experience using Java. At least 4 years ...

deployed as a Docker image into Kubernetes on AWS where we can scale on-demand to satisfy burstable workloads. We make extensive use of Kafka for low-latency communication across applications and use a mixture of different technologies for storage, from S3 to relational databases. We utilise GitHub ...

Understanding of AWS, with knowledge of Azure or GCP considered an advantage. Strong knowledge of database security, encryption and auditing practices. Experience working with Kafka environments. Excellent troubleshooting, analytical and problem-solving skills. A degree in Computer Science, Engineering or a related discipline, or equivalent practical experience. Pay range ...

Experience with Natural Language Processing (NLP), Large Language Models (LLMs) or Image Processing. Experience in areas of model development, data processing and streaming (Spark, Kafka), microservices in python (Flask or FastAPI), and interactive visualisations and User Interfaces (Streamlit, Plotly, Gradio etc). While we think the above experience ...

Experience with Natural Language Processing (NLP), Large Language Models (LLMs) or Image Processing. Experience in areas of model development, data processing and streaming (Spark, Kafka), microservices in python (Flask or FastAPI), and interactive visualisations and User Interfaces (Streamlit, Plotly, Gradio etc). While we think the above experience ...

Familiarity with AI/ML workflows and their data requirements. Experience with API specifications and data integrations acrossETL and streaming services ( Glue, MSK, Kinesis, Kafka ) Familiarity with AI developer tools like Cursor and GitHub Copilot and desire to use them to 10x your throughput. Collaborative approach and excellent communication ...

monitoring, metrics and tracing tooling - ELK stack, Splunk, Prometheus, Grafana, Graphite, OpenTSDB, OpenTrace, Jaeger Exposure to message-oriented architecture - ZeroMQ, JMS, AMPS, RabbitMQ, Kafka, Google pub/sub Exposure to process/container orchestration technologies - Mesos, Kubernetes, OpenShift, docker Hi proficiency in data architecture in both SQL and NoSQL ...

what are we looking for? Software Development: Ideally have a background in backend software development using technologies like Java, Spring Boot, AWS, GraphQL, Kafka, Docker and Kubernetes. Coaching and Mentoring: Engage, coach, mentor, facilitate, and empower team members to reach their full potential. Effective Communication: Provide context and information ...

quality, reliability, and observability. Improve the resilience and scalability of systems that support external partners and financial operations. Work with event-driven architectures, including Kafka, alongside MongoDB and MariaDB to build auditable, extensible, and performant systems. Use AI tooling in the development lifecycle to support delivery and code quality. ...

quality, reliability, and observability. Improve the resilience and scalability of systems that support external partners and financial operations. Work with event-driven architectures, including Kafka, alongside MongoDB and MariaDB to build auditable, extensible, and performant systems. Use AI tooling in the development lifecycle to support delivery and code quality. ...

experiment tracking and model management, and Airflow or Dagster for orchestrating end-to-end ML pipelines and workflows Significant experience with Data Engineering, Kafka, and stream processing technologies Proficiency in Python and SQL; experience with additional programming languages is a strong plus Excellent communication skills with the ability ...