326 to 350 of 580 Amazon S3 Jobs

Desirable Skills: Marketing Cloud experience. Certified Sales Cloud Consultant. Experience with AI models within Salesforce or other platforms. Experience with cloud platforms such as AWS, including services like Lambda, S3, or API Gateway. Familiarity with JavaScript frameworks such as React for building UI components or integrations. Knowledge of Salesforce DevOps tools (e.g., Git, Gearset, Copado, or similar). What More ❯

roles. Strong proficiency in SQL, ETL processes and database management systems (e.g., MySQL, PostgreSQL, MongoDB). Hands-on experience with AWS services for data processing, storage and analysis (e.g., S3, Redshift, EMR, Glue). Familiarity with programming languages such as Python or Java. Understanding of data warehousing concepts and data modeling techniques. Experience working with big data technologies (e.g. More ❯

design and maintenance of their back-end systems. Please apply if you have of the following: *** Amazon Web Services AWS (certifications desirable but not essential) - EC2, Autoscaling, S3, Cloudwatch, Route 53*** Linux Ubuntu, bash*** Docker/Terraform*** Chef/Puppet, Jenkins, Ansilbe*** Networking skills TCP/IP, HTTP, SSL,*** Scripting experience***Experience working with Agile methodologiesApply now More ❯

ES6+), TypeScript, React, Next.js, Redux, HTML5, CSS3/SCSS Testing: React Testing Library, Jest, Cypress (or similar) Build & Tooling: NPM, Webpack, Vite (or similar modernbundlers), Babel DevOps & Tools: AWS (S3, CloudFront, etc.), GitlabCI/CD, Git Backend Interaction: RESTful APIs (from Grails/Java services) Qualifications Must haves: 5-7+ years of proven track record in frontend development More ❯

building the next generation of finance systems onto the cloud platforms, one of the key strategies for the division in which you'll get exposure to technologies like AWS S3,Snowflake, EMR etc. Autonomy: You'll have significant autonomy in designing and writing solutions to help our stakeholders deliver for the firm's clients. Creativity: You'll be encouraged More ❯

foundational skills include: Deep proficiency in Python or JavaScript/TypeScript and associated AI/ML SDKs. Solid experience with cloud platforms, specifically AWS (including services like SageMaker, Lambda, S3). Preferred Skills We value experience with deploying and managing open-source models. Our front-end stack includes React/Next.js, so familiarity here is beneficial. Additional Skills Beyond More ❯

reusable data assets that power analytics, machine learning, and operational efficiencies. Key Responsibilities: Design, develop and maintain data pipelines and data assets within an AWS-based data lake architecture (S3, Glue, Lake Formation). Act as the technical subject matter expert on data engineering, offering in-house consultancy support to multiple business areas. Engage with data owners, security officers … training, and cross-team collaboration. Key Requirements: Essential: 3+ years' experience in a Data Engineering role, delivering high-quality, reusable data pipelines. Strong experience working within AWS environments specifically S3, Glue, Lambda, GitHub, and Terraform. Understanding of data governance, lineage tools, and cloud-based data architectures. Skilled in a range of analytics and BI tools (e.g., SQL, Alteryx, Power More ❯

and compliance with GDPR and industry regulations. What We’re Looking For 4+ years of experience in Python development (Flask, Django). Strong expertise in AWS cloud environments (EC2, S3, RDS, Redshift, Athena). Experience with SQL databases (PostgreSQL, SQLAlchemy). Knowledge of ETL pipelines, API development, and front-end technologies (HTML, CSS). Experience with Infrastructure as Code More ❯

with AI and predictive modeling experts to create impactful applications to positively impact the lives of millions of people Drive innovation using Python, FastAPI and AWS infrastructure tools (EC2, S3, RDS, Lambda, etc.), SQL/NoSQL What We're Looking For: Experience working with autonomy and taking the lead of back end development Experience improving the scalability and performance More ❯

for application operations and infrastructure. QUALIFICATIONS: • 10+ years in IT project/delivery management. • 6+ years leading Agile-based support teams. • 3+ years of AWS migration experience (EC2, RDS, S3, CloudWatch). • Strong communication and stakeholder management skills. • Experience with SQL, Spring Boot, J2EE, Docker, Kubernetes, and DevSecOps tools. • Familiarity with ColdFusion, PowerBuilder, Sybase, and SSMA for database migration. More ❯

organisation-wide initiatives and capability building Required Experience & Skills: 16+ years’ experience as an solution architecture Proven technical leadership in Spring Boot, Node.js, REST APIs and AWS (including Lambda, S3, RDS, EventBridge, ECS Fargate, Secret Manager, API Gateway etc). Experience designing event-driven, microservices-based architectures and working with event stores. Demonstrable experience delivering complex solutions for private 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 ❯

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 ❯

/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 ❯

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 ❯