1 to 25 of 437 Remote/Hybrid AWS Jobs in Wales

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

document our apis) Relational Databases (we use Postgres) Docker (we use Docker to package our code, and docker-compose to run it locally) AWS Lambda (The vast majority of our backend code is deployed as AWS Lambda functions) AWS S3 AWS RDS AWS API Gateway AWS SQS AWS SNS AWS … from experience with: Redis GCP VertexAi (we use gemini a lot) GCP BigQuery (we use it to power our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Kubernetes CircleCI DataDog Auth0 Role Based Access Control JsonSchema Pusher ...

Terraform and OpenAPI. Containerisation is a big part of empowering our teams to develop, deploy and scale their applications, but so too is using AWS Lambda and avoiding the complexity of stateful services altogether. Right tool for the job. For us, DevOps is about culture rather than roles and titles. ...

Terraform and OpenAPI. Containerisation is a big part of empowering our teams to develop, deploy and scale their applications, but so too is using AWS Lambda and avoiding the complexity of stateful services altogether. Right tool for the job. For us, DevOps is about culture rather than roles and titles. ...

experience listed below, don’t let that stop you from applying! Engineering and Data Engineering Hands-on Python experience Knowledge of cloud infrastructure like AWS, GCP or Azure Have used version control systems, specifically Git or similar tools Understanding of TDD and diverse testing methodologies, such as data quality, integration ...

Terraform and OpenAPI. Containerisation is a big part of empowering our teams to develop, deploy and scale their applications, but so too is using AWS Lambda and avoiding the complexity of stateful services altogether. Right tool for the job. For us, DevOps is about culture rather than roles and titles. ...

with data quality frameworks and implementation Experience with data visualisation tools like Power BI or Apache Superset Experience with other cloud data platforms like AWS, GCP or Oracle Experience with modern unified data platforms like Databricks or Microsoft Fabric Experience with Kubernetes for container orchestration Understanding of streaming technologies (Apache ...

with data quality frameworks and implementation Experience with data visualisation tools like Power BI or Apache Superset Experience with other cloud data platforms like AWS, GCP or Oracle Experience with modern unified data platforms like Databricks or Microsoft Fabric Experience with Kubernetes for container orchestration Understanding of streaming technologies (Apache ...

/IP networking. * Strong communication skills with the ability to build effective relationships across technical and non-technical teams. Desirable Skills: * Python and Django * AWS and Azure * Terraform * Docker, ECS and ECR * PostgreSQL (Amazon RDS) * Redis/ElastiCache * GitHub Actions, CodePipeline and CodeBuild * Elasticsearch/OpenSearch * Datadog and Logstash ...

Skills 5 plus years of experience in platform engineering, DevOps, or backend engineering, with a track record of building scalable, cloud-native environments (AWS/Kubernetes). Strong proficiency in using AI collaborators (Claude Code, Cursor, Copilot) to ship production code and an ability to optimize personal development workflows. Ability ...

Skills 5 plus years of experience in platform engineering, DevOps, or backend engineering, with a track record of building scalable, cloud-native environments (AWS/Kubernetes). Strong proficiency in using AI collaborators (Claude Code, Cursor, Copilot) to ship production code and an ability to optimize personal development workflows. Ability ...

their data, and make the most of it. Establish yourself as a trusted advisor in data driven approaches using public cloud services like AWS, Azure and GCP. Contribute to recruitment efforts and take on line management responsibilities. Skills, Knowledge & Expertise We are looking for candidates with a range of skills ...

like to hear from you: Technical Skills You have led the architectural design of systems. Highly proficient in cloud engineering (preferably in Azure; AWS and GCP) Demonstrable knowledge and experience in building solutions centred around moving and processing large amounts of data at pace and scale, using cloud-native technologies ...

like to hear from you: Technical Skills You have led the architectural design of systems. Highly proficient in cloud engineering (preferably in Azure; AWS and GCP) Demonstrable knowledge and experience in building solutions centred around moving and processing large amounts of data at pace and scale, using cloud-native technologies ...