101 to 125 of 587 Permanent Kafka Jobs

experience. Experience with Palantir Foundry (full training provided). Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. More ❯

experience. Experience with Palantir Foundry (full training provided). Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. More ❯

problem-solving skills Comfort working within a globally-distributed team A background in some of the following (bonus): Java experience Python experience Ruby experience Big data technologies: Spark, Trino, Kafka Financial Markets experience SQL: Postgres, Oracle Cloud-native deployments: AWS, Docker, Kubernetes Observability: Splunk, Prometheus, Grafana California residents, please review the California Privacy Notice for information about certain legal More ❯

like C# and/or Go are a plus), Hands-on knowledge of Docker, Kubernetes, Git, CI/CD tools, and infrastructure-as-code principles, Familiarity with messaging systems (Kafka, RabbitMQ or others) and data modeling (SQL & NoSQL), Deep understanding of secure coding, IAM protocols, and compliance frameworks, Excellent analytical, leadership, and communication skills, Fluent in English; knowledge of More ❯

Falcon LogScale (formerly Humio) • Database management systems: PostgreSQL, ClickHouse Deployment tools: Flux, Helm, Kustomize Frontend frameworks: React, Angular Infrastructure as code: Terraform, Terragrunt Cloud provider: AWS Event streaming platform: Kafka Big data processing: Databricks About Chainalysis Blockchain technology is powering a growing wave of innovation. Businesses and governments around the world are using blockchains to make banking more efficient More ❯

Continuous Integration and Continuous Deployment techniquesDESIRABLE:• Experience of performance tuning• Experience of data visualisation and complex data transformations• Experience with steaming and event-processing architectures including technologies such as Kafka and change-data-capture (CDC) products• Expertise in continuous improvement and sharing input on data best practice.# Embracing our differences At Kainos, we believe in the power of diversity More ❯

AWS) for deploying and managing backend infrastructure. Nice-to-Haves Experience integrating multiple data backends, such as combining SQL with NoSQL (e.g., MongoDB, Cosmos DB) or streaming systems (e.g., Kafka). Familiarity with containerization (Docker, Kubernetes) and serverless architectures. Contributions to open-source projects or publications on distributed systems, DDD, or backend scalability. Prior experience at a similar seniority More ❯

work in fast-paced environments. Excellent communication and stakeholder management skills. Preferred Qualifications: Experience with machine learning data pipelines and MLOps practices. Knowledge of data streaming technologies such as Kafka or Kinesis. Familiarity with Terraform or similar infrastructure automation tools. Previous experience working in consulting or client-facing roles. What We Offer: Competitive compensation, including performance-based incentives. Opportunities More ❯

work in fast-paced environments. Excellent communication and stakeholder management skills. Preferred Qualifications: Experience with machine learning data pipelines and MLOps practices. Knowledge of data streaming technologies such as Kafka or Kinesis. Familiarity with Terraform or similar infrastructure automation tools. Previous experience working in consulting or client-facing roles. What We Offer: Competitive compensation, including performance-based incentives. Opportunities More ❯

data governance processes.  Experience with version control systems (e.g., Git).  Experience with Agile development methodologies.  Excellent communication, interpersonal, and problem-solving skills.  Experience with streaming data technologies (e.g., Kafka, Azure Event Hubs).  Experience with data visualisation tools (e.g., Tableau, Power BI).  Experience with DevOps tools and practices (e.g., Azure DevOps, Jenkins, Docker, Kubernetes).  Experience working More ❯

product engineering background to join their team, building highly available, scalable systems that power next-generation payments. Your Background/Tech Stack Java with Spring Reactive programming (AKKA etc) Kafka or JMS Solid understanding of CI/CD pipelines, automation, and Agile delivery practices. Experience working with MongoDB or other NoSQL databases. The Role Play a key role in More ❯

product engineering background to join their team, building highly available, scalable systems that power next-generation payments. Your Background/Tech Stack Java with Spring Reactive programming (AKKA etc) Kafka or JMS Solid understanding of CI/CD pipelines, automation, and Agile delivery practices. Experience working with MongoDB or other NoSQL databases. The Role Play a key role in More ❯

sprints, each engineer is responsible for writing their own test scripts to achieve full automation Required Skills/Experience: The ideal candidate will have the following: • Java, Spring, Hibernate • Kafka • Linux, VMware, Openshift, AWS • CI/CD Pipelines via Jenkins, Github Actions, Chef, Ansible, Nexus • Testing of Database technologies (Postgres or similar) • Full end to end quality tool-set More ❯

testable, and well-documented code that stands the test of time. Contribute to architecture discussions and influence key technical decisions. Tech Stack Java 17+, Spring WebFlux/Project Reactor, Kafka, PostgreSQL, Docker, Kubernetes, AWS. Exposure to distributed systems, event-driven architecture, and microservices is highly valued Working Model 1-2 days per week in our London office, 3 days More ❯

testable, and well-documented code that stands the test of time. Contribute to architecture discussions and influence key technical decisions. Tech Stack Java 17+, Spring WebFlux/Project Reactor, Kafka, PostgreSQL, Docker, Kubernetes, AWS. Exposure to distributed systems, event-driven architecture, and microservices is highly valued Working Model 1-2 days per week in our London office, 3 days More ❯

of professional experience in backend software development (with at least 1–2 years using Golang). Solid understanding of distributed systems , concurrency , and API design . Experience with PostgreSQL , Kafka , Redis , or similar technologies. Familiarity with Docker , Kubernetes , and cloud platforms (AWS, GCP, or Azure). Strong problem-solving skills and attention to performance and reliability. Bonus points for More ❯

of professional experience in backend software development (with at least 1–2 years using Golang). Solid understanding of distributed systems , concurrency , and API design . Experience with PostgreSQL , Kafka , Redis , or similar technologies. Familiarity with Docker , Kubernetes , and cloud platforms (AWS, GCP, or Azure). Strong problem-solving skills and attention to performance and reliability. Bonus points for More ❯

preferred) including S3, Redshift, Glue, Lambda Familiarity with data warehousing (Redshift, Snowflake, BigQuery) Experience with workflow orchestration tools (Airflow, Dagster, Prefect) Understanding of distributed systems, batch and streaming data (Kafka, Kinesis) Knowledge of IaC (Terraform, CloudFormation) and containerisation (Docker, Kubernetes) Nice to have: Experience with dbt, feature stores, or ML pipeline tooling Familiarity with Elasticsearch or real-time analytics More ❯

preferred) including S3, Redshift, Glue, Lambda Familiarity with data warehousing (Redshift, Snowflake, BigQuery) Experience with workflow orchestration tools (Airflow, Dagster, Prefect) Understanding of distributed systems, batch and streaming data (Kafka, Kinesis) Knowledge of IaC (Terraform, CloudFormation) and containerisation (Docker, Kubernetes) Nice to have: Experience with dbt, feature stores, or ML pipeline tooling Familiarity with Elasticsearch or real-time analytics More ❯

and general knowledge of the framework) Experience in building complex, large-scale software solutions from scratch to live production Experience with Java, Spring Boot, Spring Data, JPA, Swagger, Maven, Kafka, PostgreSQL, Jenkins, GIT, RESTful Services, Docker Strong analytical skills Self-starter, fast learner, and great interpersonal skills Excellent English communication skills – spoken and written Financial affinity is an advantage More ❯

and general knowledge of the framework) Experience in building complex, large-scale software solutions from scratch to live production Experience with Java, Spring Boot, Spring Data, JPA, Swagger, Maven, Kafka, PostgreSQL, Jenkins, GIT, RESTful Services, Docker Strong analytical skills Self-starter, fast learner, and great interpersonal skills Excellent English communication skills – spoken and written Financial affinity is an advantage More ❯

expertise with GCP including BigQuery, Pub/Sub, Cloud Composer and IAM You have strong Python, SQL and PySpark skills You have experience with real-time data streaming using Kafka or Spark You have a good knowledge of Data Lakes, Data Warehousing, Data Modelling You're familiar with DevOps principles, containerisation and CI/CD tools such as Jenkins More ❯

expertise with GCP including BigQuery, Pub/Sub, Cloud Composer and IAM You have strong Python, SQL and PySpark skills You have experience with real-time data streaming using Kafka or Spark You have a good knowledge of Data Lakes, Data Warehousing, Data Modelling You're familiar with DevOps principles, containerisation and CI/CD tools such as Jenkins More ❯

team of engineers across multiple global locations. Drive architectural improvements, performance optimisation, and best engineering practices. Technology Environment Languages: Python Architecture: Cloud-native, containerised microservices (Kubernetes, Docker). Infrastructure: Kafka, Terraform, Jenkins, Git, CI/CD pipelines. Data: SQL/NoSQL databases, distributed data processing, data lake environments. Quant Integration: Comfortable working with quant libraries and APIs. Ideal Profile More ❯

team of engineers across multiple global locations. Drive architectural improvements, performance optimisation, and best engineering practices. Technology Environment Languages: Python Architecture: Cloud-native, containerised microservices (Kubernetes, Docker). Infrastructure: Kafka, Terraform, Jenkins, Git, CI/CD pipelines. Data: SQL/NoSQL databases, distributed data processing, data lake environments. Quant Integration: Comfortable working with quant libraries and APIs. Ideal Profile More ❯