226 to 250 of 1,064 Kafka Jobs

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 ❯

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 ❯

and observability frameworks, including lineage tracking, SLAs, and data quality monitoring. Familiarity with modern data lake table formats such as Delta Lake, Iceberg, or Hudi. Background in stream processing (Kafka, Flink, or similar ecosystems). Exposure to containerisation and orchestration technologies such as Docker and Kubernetes. More ❯

for data workflows. Excellent communication skills and ability to collaborate across teams. Preferred Qualifications Experience with Databricks Unity Catalog and Delta Live Tables. Familiarity with streaming frameworks (Structured Streaming, Kafka, etc.). Background in data observability and metadata management. Exposure to machine learning pipelines or MLflow within Databricks. Knowledge of infrastructure as code (IaC) using Terraform or similar tools. More ❯

for data workflows. Excellent communication skills and ability to collaborate across teams. Preferred Qualifications Experience with Databricks Unity Catalog and Delta Live Tables. Familiarity with streaming frameworks (Structured Streaming, Kafka, etc.). Background in data observability and metadata management. Exposure to machine learning pipelines or MLflow within Databricks. Knowledge of infrastructure as code (IaC) using Terraform or similar tools. More ❯

for data workflows. Excellent communication skills and ability to collaborate across teams. Preferred Qualifications Experience with Databricks Unity Catalog and Delta Live Tables. Familiarity with streaming frameworks (Structured Streaming, Kafka, etc.). Background in data observability and metadata management. Exposure to machine learning pipelines or MLflow within Databricks. Knowledge of infrastructure as code (IaC) using Terraform or similar tools. More ❯

for data workflows. Excellent communication skills and ability to collaborate across teams. Preferred Qualifications Experience with Databricks Unity Catalog and Delta Live Tables. Familiarity with streaming frameworks (Structured Streaming, Kafka, etc.). Background in data observability and metadata management. Exposure to machine learning pipelines or MLflow within Databricks. Knowledge of infrastructure as code (IaC) using Terraform or similar tools. More ❯

for data workflows. Excellent communication skills and ability to collaborate across teams. Preferred Qualifications Experience with Databricks Unity Catalog and Delta Live Tables. Familiarity with streaming frameworks (Structured Streaming, Kafka, etc.). Background in data observability and metadata management. Exposure to machine learning pipelines or MLflow within Databricks. Knowledge of infrastructure as code (IaC) using Terraform or similar tools. More ❯

for data workflows. Excellent communication skills and ability to collaborate across teams. Preferred Qualifications Experience with Databricks Unity Catalog and Delta Live Tables. Familiarity with streaming frameworks (Structured Streaming, Kafka, etc.). Background in data observability and metadata management. Exposure to machine learning pipelines or MLflow within Databricks. Knowledge of infrastructure as code (IaC) using Terraform or similar tools. More ❯

for data workflows. Excellent communication skills and ability to collaborate across teams. Preferred Qualifications Experience with Databricks Unity Catalog and Delta Live Tables. Familiarity with streaming frameworks (Structured Streaming, Kafka, etc.). Background in data observability and metadata management. Exposure to machine learning pipelines or MLflow within Databricks. Knowledge of infrastructure as code (IaC) using Terraform or similar tools. More ❯

/CD, and cloud deployment workflows. Practical experience with MongoDB or similar NoSQL databases. Problem-solver with strong communication skills and a collaborative mindset. Bonus: experience with message queues (Kafka, RabbitMQ), observability tooling, or DevOps-style environments. Why You'll Love It Here Impact & Ownership - You'll own core backend systems and shape architectural decisions. Modern Tech Stack - Node.js More ❯

/CD, and cloud deployment workflows. Practical experience with MongoDB or similar NoSQL databases. Problem-solver with strong communication skills and a collaborative mindset. Bonus: experience with message queues (Kafka, RabbitMQ), observability tooling, or DevOps-style environments. 🌟 Why You’ll Love It Here Impact & Ownership — You’ll own core backend systems and shape architectural decisions. Modern Tech Stack — Node.js More ❯

/CD, and cloud deployment workflows. Practical experience with MongoDB or similar NoSQL databases. Problem-solver with strong communication skills and a collaborative mindset. Bonus: experience with message queues (Kafka, RabbitMQ), observability tooling, or DevOps-style environments. 🌟 Why You’ll Love It Here Impact & Ownership — You’ll own core backend systems and shape architectural decisions. Modern Tech Stack — Node.js More ❯

/CD, and cloud deployment workflows. Practical experience with MongoDB or similar NoSQL databases. Problem-solver with strong communication skills and a collaborative mindset. Bonus: experience with message queues (Kafka, RabbitMQ), observability tooling, or DevOps-style environments. 🌟 Why You’ll Love It Here Impact & Ownership — You’ll own core backend systems and shape architectural decisions. Modern Tech Stack — Node.js More ❯

/CD, and cloud deployment workflows. Practical experience with MongoDB or similar NoSQL databases. Problem-solver with strong communication skills and a collaborative mindset. Bonus: experience with message queues (Kafka, RabbitMQ), observability tooling, or DevOps-style environments. 🌟 Why You’ll Love It Here Impact & Ownership — You’ll own core backend systems and shape architectural decisions. Modern Tech Stack — Node.js More ❯

/CD, and cloud deployment workflows. Practical experience with MongoDB or similar NoSQL databases. Problem-solver with strong communication skills and a collaborative mindset. Bonus: experience with message queues (Kafka, RabbitMQ), observability tooling, or DevOps-style environments. 🌟 Why You’ll Love It Here Impact & Ownership — You’ll own core backend systems and shape architectural decisions. Modern Tech Stack — Node.js More ❯

with data security, privacy, and compliance frameworks ● Exposure to machine learning pipelines, MLOps, or AI-driven data products ● Experience with big data platforms and technologies such as EMR, Databricks, Kafka, Spark ● Exposure to AI/ML concepts and collaboration with data science or AI teams. ● Experience integrating data solutions with AI/ML platforms or supporting AI-driven analytics More ❯

with data security, privacy, and compliance frameworks ● Exposure to machine learning pipelines, MLOps, or AI-driven data products ● Experience with big data platforms and technologies such as EMR, Databricks, Kafka, Spark ● Exposure to AI/ML concepts and collaboration with data science or AI teams. ● Experience integrating data solutions with AI/ML platforms or supporting AI-driven analytics More ❯

a nutshell 5 + years building production-grade Python systems for data-heavy businesses; comfortable with tests, version control and optimisation. Confident SQL , exposure to REST and messaging (Rabbit, Kafka, etc.), and enough Linux to troubleshoot on the command line. UI chops in Dash, Flask or React to whip up proof-of-concept dashboards. Solid grounding in financial products More ❯

a nutshell 5 + years building production-grade Python systems for data-heavy businesses; comfortable with tests, version control and optimisation. Confident SQL , exposure to REST and messaging (Rabbit, Kafka, etc.), and enough Linux to troubleshoot on the command line. UI chops in Dash, Flask or React to whip up proof-of-concept dashboards. Solid grounding in financial products More ❯

Cloud technologies and how to create scalable multi-region applications Experience with the following technologies: AWS Serverless and serverless-supported languages DB (ex, Postgresql, CocroachDB) Streaming technologies (Amazon Kinesis, Kafka) Message Queues (SQS, RabbitMQ, ActiveMQ) Experience working within an agile development Experience with containerization (Docker, Kubernetes, etc) Experience with Micro-Service and Service oriented architectures Experience with Core Services More ❯

and SageMaker Understanding of DevOps processes and tools: CI/CD, Docker, Terraform, and monitoring/observability Bonus: experience with vector databases, semantic search, or event-driven systems like Kafka Additional Information Were a community here that cares as much about your life outside work as how you feel when youre with us. Because your job shouldnt take over More ❯

systems and RESTful or event driven APIs. Familiarity with cloud platforms such as AWS or GCP, and related infrastructure services. Understanding of data streaming, message queues, or asynchronous processing (Kafka, Pub/Sub, SQS). Proficiency with relational and/or NoSQL databases and writing performant queries. Solid grasp of software engineering best practices, including testing, CI/CD More ❯

for mobile or web clients. Deep experience with distributed systems, microservices architecture, and event-driven patterns. Demonstrated experience with real-time applications and data streaming technologies (e.g., WebSockets, gRPC, Kafka). Experience integrating third-party AI/ML APIs (e.g., LLMs, STT/TTS, or other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/ More ❯