76 to 100 of 365 Remote DynamoDB Jobs

skills and experience Node.js and TypeScript. AWS and serverless application development. REST API design and development. Event-driven architectures (SNS, SQS or similar). DynamoDB and JSON data processing. Infrastructure as Code (Terraform, CDK, SST or similar). CI/CD pipelines and modern software delivery practices. Experience building ...

adoption, and performance metrics.QUALIFICATIONSSkills and AbilitiesStrong experience with Python for backend development Proven expertise in AWS Serverless technologies: Lambda, API Gateway, AppSync, Step Functions, DynamoDB, etc. Strong experience with microservices architecture and event-driven systems Hands-on experience with Infrastructure as Code (IaC) tools such ...

adoption, and performance metrics.QUALIFICATIONSSkills and AbilitiesStrong experience with Python for backend development Proven expertise in AWS Serverless technologies: Lambda, API Gateway, AppSync, Step Functions, DynamoDB, etc. Strong experience with microservices architecture and event-driven systems Hands-on experience with Infrastructure as Code (IaC) tools such ...

including serverless architecture (Lambda, API Gateway), container orchestration (EKS), messaging (SNS/SQS, RabbitMQ), and data services (RDS PostgreSQL, ElastiCache/Redis, DynamoDB). Manage and evolve CI/CD pipelines - automating build, test, and deployment processes using GitLab CI, Gradle, Terraform, and Serverless Framework to enable rapid, consistent … without compromising code quality or security standards. Extensive hands-on experience with AWS - specifically Lambda, API Gateway, CloudFront, S3, SNS, SQS, EKS, ElastiCache, and DynamoDB - and a track record of deploying and operating production workloads in cloud environments. Advanced proficiency with PostgreSQL and other data stores (Redis/Valkey ...

including serverless architecture (Lambda, API Gateway), container orchestration (EKS), messaging (SNS/SQS, RabbitMQ), and data services (RDS PostgreSQL, ElastiCache/Redis, DynamoDB). Manage and evolve CI/CD pipelines - automating build, test, and deployment processes using GitLab CI, Gradle, Terraform, and Serverless Framework to enable rapid, consistent … without compromising code quality or security standards. Extensive hands-on experience with AWS - specifically Lambda, API Gateway, CloudFront, S3, SNS, SQS, EKS, ElastiCache, and DynamoDB - and a track record of deploying and operating production workloads in cloud environments. Advanced proficiency with PostgreSQL and other data stores (Redis/Valkey ...

cloud and contact centre expertise. Skills Knowledge and Expertise Extensive experience with Amazon Connect. Extensive experience with AWS services i.e. Lambda, CloudWatch , API Gateway, DynamoDB, IAM and S3. Extensive experience with contact center standards and systems. Strong understanding of CCaaS platforms and customer experience solutions. Extensive experience in consultative ...

system design and distributed systems knowledge You have experience with SQL and relational databases You have experience with production AWS - CI/CD, SQS, DynamoDB, S3, ECS or Lambda advantageous You have a good understanding of microservices and event driven architectures You're comfortable taking technical ownership and mentoring ...

/Serverless development REST APIs Spring Boot JUnit 5 Linux/Shell scripting Git and CI/CD experience Desirable Skills AWS API Gateway DynamoDB SQS IAM CloudWatch Oracle Database Mockito, Cucumber, WireMock OAuth/SSO experience Experience Strong Java backend development experience. Experience building and deploying applications ...

/Serverless development REST APIs Spring Boot JUnit 5 Linux/Shell scripting Git and CI/CD experience Desirable Skills AWS API Gateway DynamoDB SQS IAM CloudWatch Oracle Database Mockito, Cucumber, WireMock OAuth/SSO experience Experience Strong Java backend development experience. Experience building and deploying applications ...

Vue.js, React or modern Angular You have a good knowledge of SQL and relational databases You have production experience with AWS, ideally including SQS, DynamoDB, S3, ECS and Lambda You have experience owning CI/CD and release processes, such as GitHub Actions You have hands-on experience with ...

like - Hive/Hadoop, Apache SparkExperience in developing Finance or HR related applicationsExperience with following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, LambdaWorking experience with TerraformExperience in creating workflows for Apache Airflow#LI-GL1What's Roku's approach to hybrid working? Roku fosters ...

like - Hive/Hadoop, Apache SparkExperience in developing Finance or HR related applicationsExperience with following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, LambdaWorking experience with TerraformExperience in creating workflows for Apache Airflow#LI-GL1What's Roku's approach to hybrid working? Roku fosters ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...