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Event Streaming, Kafka, MSK, Azure Event Hubs. Cloud: AWS, GCP, Microservices, Containers, Docker, Kubernetes. batch manner (Kafka Streams, Apache Flink) DevSecOps CICD Pipelines: Urban Code Deploy, EDSE Pipeline (Cloudbees Core) aka Cloudbees Jenkins, Rancher.
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Extensive hands-on experience implementing data migration and data processing using AWS services: VPC/SG, EC2, S3, Autoscaling, CloudFormation, Lake Formation, DMS, Kinesis, Kafka, Nifi, CDC processing Redshift, Snowflake, RDS, Aurora, Neptune, DynamoDB, CloudTrail, CloudWatch, Docker, Lambda, Spark, Glue, Sage Maker, AI/Client, API GW, etc.
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DevSecOps : GitOps, Jira, Git/GitLab/GitHub, Docker, CI/CD, Kubernetes, Jenkins, Kafka/Zookeeper, Consul. Core Technologies Kubernetes (Rancher), Docker, Chef. DevSecOps : GitOps, Jira, Git/GitLab/GitHub, Docker, CI/CD, Kubernetes, Jenkins, Kafka/Zookeeper, Consul.
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Java Spring Boot, Spring, Maven, Docker, RESTful Services, XML, JSON, MongoDB, Kubernetes/Rancher, Kafka, Python and Amazon S3. ·Docker, Rancher, 508 Compliance. Java Spring Boot, Spring, Maven, Docker, RESTful Services, XML, JSON, MongoDB, Kubernetes/Rancher, Kafka, Python and Amazon S3.
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Prior experience with data engineering tools and frameworks like Airflow, Kafka, Hadoop, Spark, Kubernetes. Comfortable with DevOps tools like AWS Cloud Formation/Terraform, Docker and Git for CI/CD development.
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Experience with Sagemaker AWS, Kafka, Python, R, SQL and NoSQL Databases, Spark, Scikit-Learn, Keras/TensorFlow, PyTorch, Docker, CI/CD Pipelines, Git, or developing APIs. Experience with Sagemaker AWS, Kafka, Python, R, SQL and NoSQL Databases, Spark, Scikit-Learn, Keras/TensorFlow, PyTorch, Docker, CI/CD Pipelines, Git, or developing APIs.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Cloud platform knowledge (e.g., AWS, Azure) and experience building distributed systems through technologies like microservices, containers and orchestration tools (e.g., Docker, Kubernetes) + Advanced Java frameworks and libraries like Spring Boot, Apache Kafka, or Apache Camel.
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Possess in-depth knowledge and hands-on experience with DevOps tools and technologies, including but not limited to GitHub, Jenkins, Terraform, Docker, Ansible, Kafka, AWS, Apigee. Experience with Kafka MRC.
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We use Kafka for data pipelines, Apache Beam for ETL, Bitbucket for source control, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, ELK for log shipping and monitoring, Docker for containerisation, Kubernetes for container orchestration, OpenStack for our private cloud, Ansible for architecture automation, and Slack for internal communication.
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The candidate is expected to have experience with Jenkins, Ansible, Ansible Tower, OpenStack, Docker, Kafka, Hadoop Spark, automation, software engineering, Jira, Confluence, and Power BI reporting.
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Experience with containers (Kubernetes, ECS, EC2, Docker, Podman, etc.) Experience with distributed data streaming frameworks like Spark Structured Streaming, Apache Flink, Kafka, etc. Experience with AWS (API Gateway, RDS, Redshift, S3, SQS, SNS, SES, Route 53, CloudFront, CloudWatch), React, TypeScript, Terraform, and Linux.
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This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform.
$182,400 - $247,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with Kafka, NiFi, MuleSoft, Boomi or other integration technologies. Experience with containerization technologies such as Docker, Kubernetes, or OpenShift. Web development experience with React, Vue.js, Angular, or other technologies.
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You are a driven data engineer with experience working with big data technologies such as Docker, ECS, S3, Redshift, Kafka, and RDS. You are a driven data engineer with experience working with big data technologies such as Docker, ECS, S3, Redshift, Kafka, and RDS.
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