526 to 550 of 883 Amazon S3 Jobs

decisions. Key Experience Required: Expertise in SQL Server (approx. 75% of the role) including performance tuning, data warehousing, and reporting. Experience with AWS data services (approx. 25%), particularly RDS, S3, Lambda, EventBridge, and building data pipelines in cloud-native environments. Proven delivery of dimensional/Kimball data models in collaboration with Data Analysts. Strong proficiency with Power BI, including More ❯

decisions. Key Experience Required: Expertise in SQL Server (approx. 75% of the role) including performance tuning, data warehousing, and reporting. Experience with AWS data services (approx. 25%), particularly RDS, S3, Lambda, EventBridge, and building data pipelines in cloud-native environments. Proven delivery of dimensional/Kimball data models in collaboration with Data Analysts. Strong proficiency with Power BI, including More ❯

decisions. Key Experience Required: Expertise in SQL Server (approx. 75% of the role) including performance tuning, data warehousing, and reporting. Experience with AWS data services (approx. 25%), particularly RDS, S3, Lambda, EventBridge, and building data pipelines in cloud-native environments. Proven delivery of dimensional/Kimball data models in collaboration with Data Analysts. Strong proficiency with Power BI, including More ❯

excellent oral and written communication skills. Understanding of custom code development/reviews Experience with GITLAB functionality, error codes and scripting Experience using AWS services/technologies (e.g. CloudFormation, S3, ECS, EKS) Experience with AWS Serverless architectures (lambda, API gateway, load balancing, autoscaling) Experience supporting development testing Experience with cloud-based architectures Understanding of DevSecOps methodologies and workflow Experience More ❯

/ELT processes, automation Technical Requirements: - Strong proficiency in SQL and Python programming - Extensive experience with data modeling and data warehouse concepts - Advanced knowledge of AWS data services, including: S3, Redshift, AWS Glue, AWS Lambda - Experience with Infrastructure as Code using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required More ❯

/ELT processes, automation Technical Requirements: - Strong proficiency in SQL and Python programming - Extensive experience with data modeling and data warehouse concepts - Advanced knowledge of AWS data services, including: S3, Redshift, AWS Glue, AWS Lambda - Experience with Infrastructure as Code using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required More ❯

/ELT processes, automation Technical Requirements: - Strong proficiency in SQL and Python programming - Extensive experience with data modeling and data warehouse concepts - Advanced knowledge of AWS data services, including: S3, Redshift, AWS Glue, AWS Lambda - Experience with Infrastructure as Code using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required More ❯

/ELT processes, automation Technical Requirements: - Strong proficiency in SQL and Python programming - Extensive experience with data modeling and data warehouse concepts - Advanced knowledge of AWS data services, including: S3, Redshift, AWS Glue, AWS Lambda - Experience with Infrastructure as Code using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required More ❯

knowledge of various data access patterns and underlying technology implementations. Properly secure the data from unauthorized access at multiple data access points (e.g. search discovery rules, repository read rules, S3 bucket policies, etc). Apply your excellent knowledge of the AWS ecosystem to support both the existing infrastructure (built on EC2 with Terraform) and to help us build the More ❯

an agile software development environment. Experience of source control (e.g., git) and issue tracking (e.g., JIRA) tools. Experience of object orientated programming principles. Experience of AWS (e.g., Lambda, Cognito, S3, DynamoDB). Demonstrated ability to share knowledge, concepts, and ideas to a wide range of people. Excellent written and verbal communication with strong interpersonal skills. Experience in mentoring others. More ❯

and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. Full-Stack More ❯

and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. Full-Stack More ❯

and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. Full-Stack More ❯

and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. Full-Stack More ❯

and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. Full-Stack More ❯

and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. Full-Stack More ❯

and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. Full-Stack More ❯

as domain-driven design, event-driven systems, micro-frontends, and microservices. Ability to lead and partner with internal and external technical resources. Experience with cloud services including AWS EC2, S3, SQS, Lambda, RDS, and Grafana. Knowledge of web security practices including XSS, CSRF, and secure coding standards. Strong communication, interpersonal, and presentation skills suitable for diverse audiences. Learn more More ❯

excellent oral and written communication skills. Understanding of custom code development/reviews Experience with GITLAB functionality, error codes and scripting Experience using AWS services/technologies (e.g. CloudFormation, S3, ECS, EKS) Experience with AWS Serverless architectures (lambda, API gateway, load balancing, autoscaling) Experience supporting development testing Experience with cloud-based architectures Understanding of DevSecOps methodologies and workflow Experience More ❯

excellent oral and written communication skills. Understanding of custom code development/reviews Experience with GITLAB functionality, error codes and scripting Experience using AWS services/technologies (e.g. CloudFormation, S3, ECS, EKS) Experience with AWS Serverless architectures (lambda, API gateway, load balancing, autoscaling) Experience supporting development testing Experience with cloud-based architectures Understanding of DevSecOps methodologies and workflow Experience More ❯

RESTful architecture Proven ability to mentor and uplift teammates technically Excellent problem-solving skills and the ability to work independently Bonus Experience Knowledge of AWS services (e.g., EC2, RDS, S3) Familiar with Docker/containerisation and orchestration Experience with test automation (PHPUnit, Pest) Understanding of microservices or event-driven architectures The Perks Flexible working: remote-first with optional hybrid More ❯

the ability to purchase more Share options Private health insurance What's required to be successful in this role? Proven experience with AWS cloud services and architecture design, specifically S3 and EC2 Strong hands-on skills in Infrastructure-as-Code, especially with Terraform. Experience with Ansible for configuration management. Solid understanding of Linux systems - specifically Ubuntu Knowledge of containerisation More ❯

such as Pytorch, TensorFlow. Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models, experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2, hands-on experience of building ML solutions on AWS. Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to More ❯

infrastructure tailored to financial management workloads. Develop and manage Infrastructure as Code (IaC) solutions using Terraform, AWS CloudFormation, or similar tools. Configure and maintain AWS services including EC2, RDS, S3, VPC, IAM, Transit Gateway, CloudWatch, CloudTrail, etc. Ensure full alignment with client Risk Management Framework and cloud policy requirements. Collaborate with development, cybersecurity, and financial systems teams to validate More ❯

engage with stakeholders to maximise the value of data assets. Key Requirements Essential: Demonstrable experience leading the delivery of robust and reusable data pipelines using AWS technologies such as S3, Glue, Lambda, and Lake Formation. Proficiency in Terraform, GitHub, and VS Code for pipeline deployment. Proven leadership in developing high-performing data teams. Strong SQL and familiarity with analytics More ❯