101 to 125 of 155 Permanent Amazon S3 Jobs

data management. Experience in developing data analytics and AI-driven solutions. Skilled in designing and automating data quality metrics and KPIs. Proficient with AWS (S3, Kinesis, Glue, Redshift, Lambda, EMR) and/or Azure (ADF, Synapse, Fabric, Functions). To be Considered.... Please either apply by clicking online ...

with multi-tenant architecture, shared packages, and distributed systems *Solid understanding of OAuth 2.1, identity systems, and backend security *Experience with AWS (EC2, RDS, S3), Docker, CI/CD, and Laravel Forge or Vapor *Comfortable working with Elasticsearch, async pipelines, and event-driven design Rise Technical Recruitment Ltd acts ...

loosely defined features from concept to production Strong communication skills; thrives in a small, collaborative team Nice to Have AWS (EKS/Kubernetes, Helm, S3, SES, IAM) Auth0, Keycloak or other OAuth2/OIDC providers Compliance, KYC/AML, fintech or other regulated-industry experience Payment provider integration (e.g. ...

data platforms such as Databricks and Snowflake Good understanding of AWS data analytics services, including Redshift, EMR, Glue, Athena, Kinesis, Lake Formation, MSK, and S3 data lake patterns, with demonstrated experience architecting end-to-end data solutions Experience navigating complex data governance, security, and compliance requirements across multi-cloud ...

data platforms such as Databricks and Snowflake Good understanding of AWS data analytics services, including Redshift, EMR, Glue, Athena, Kinesis, Lake Formation, MSK, and S3 data lake patterns, with demonstrated experience architecting end-to-end data solutions Experience navigating complex data governance, security, and compliance requirements across multi-cloud ...

such as Databricks and Snowflake\ N\n\nGood understanding of AWS data analytics services, including Redshift, EMR, Glue, Athena, Kinesis, Lake Formation, MSK, and S3 data lake patterns, with demonstrated experience architecting end-to-end data solutions\ N\n\nExperience navigating complex data governance, security, and compliance requirements across ...

primary backend language High-level frameworks (Flask, SQLAlchemy, Alembic, Pytest, Socket.IO) Amazon Web Services and ecosystem (AWS core services, Lambda, RDS, EKS, S3, etc.) Cloud-native technologies (Kubernetes, Helm, Docker) Observability technologies (Prometheus, Jaeger, Loki, Grafana, Sentry) Infrastructure automation and containerized CI/CD (GitLab, Terraform, Atlantis ...

other relevant field and demonstrable related experience.\ NExtensive experiencein DevOps or cloud infrastructure roles.\ NStrong AWS expertise, including services such as IAM, EC2, S3, Lambda, and RDS.\ NContainerization proficiency, particularly Kubernetes and hosting platforms such as EKS.\ NExperience deployingand maintaining database technologies, including Amazon RDS, Aurora ...

work streams focused on AI infrastructure and tooling. What will you bring to the table? Experience working with cloud platforms like AWS (EC2, ECS, S3, Lambda, Fargate, DynamoDB/RDS) or GCP (Compute Engine, Cloud Storage, Cloud Functions, BigQuery). Strong experience in Python and fluency in another language.Knowledge … date with new technology in the AI space. Nice to have: Direct experience with advanced AI tools and platforms, such as Amazon Bedrock or Google Vertex AI. Familiarity with frameworks for building complex, multi-step generative AI applications, like LangGraph.Experience with Agent-to-Agent (A2A) communication or coordination ...

infrastructure and tooling. \n\n What will you bring to the table? \n \n Experience working with cloud platforms like AWS (EC2, ECS, S3, Lambda, Fargate, DynamoDB/RDS) or GCP (Compute Engine, Cloud Storage, Cloud Functions, BigQuery). \n Strong experience in Python and fluency in another language. … technology in the AI space. \n\n Nice to have: \n \n Direct experience with advanced AI tools and platforms, such as Amazon Bedrock or Google Vertex AI. \n Familiarity with frameworks for building complex, multi-step generative AI applications, like LangGraph. \n Experience with Agent-to-Agent ...

streams focused on AI infrastructure and tooling.\ N\nWhat will you bringto the table?\ N\nExperience working with cloud platforms like AWS (EC2, ECS, S3, Lambda, Fargate, DynamoDB/RDS) or GCP (Compute Engine, Cloud Storage, Cloud Functions, BigQuery).\ NStrong experience inPython and fluency in another language.\ NKnowledge … date with new technology in the AI space.\ N\nNice to have:\ N\nDirect experience with advanced AI tools and platforms, such as Amazon Bedrock or Google Vertex AI.\ NFamiliarity with frameworks for building complex, multi-step generative AI applications, like LangGraph.\ NExperience with Agent-to-Agent ...

work streams focused on AI infrastructure and tooling. What will you bring to the table? Experience working with cloud platforms like AWS (EC2, ECS, S3, Lambda, Fargate, DynamoDB/RDS) or GCP (Compute Engine, Cloud Storage, Cloud Functions, BigQuery). Strong experience in Python and fluency in another language. … date with new technology in the AI space. Nice to have: Direct experience with advanced AI tools and platforms, such as Amazon Bedrock or Google Vertex AI. Familiarity with frameworks for building complex, multi-step generative AI applications, like LangGraph. Experience with Agent-to-Agent (A2A) communication ...

real ownership of technical delivery. What you’ll be doing AWS Cloud Engineering Designing and building serverless applications using AWS Lambda, API Gateway, DynamoDB, S3, SQS, and SNS. Developing scalable microservices and event-driven systems using Node.js and/or TypeScript. Owning features end-to-end including design, build … testing, deployment, and production support. Building and maintaining secure, high-performance REST and event-driven APIs. Designing efficient data models in DynamoDB and managing S3-based storage patterns. Infrastructure & CI/CD Building infrastructure as code using AWS CDK, Terraform, or CloudFormation. Developing and improving CI/CD pipelines ...

engineering teams throughout the full software development lifecycle. Key responsibilities include: Designing and developing serverless applications using AWS services including Lambda, API Gateway, DynamoDB, S3, SQS, and SNS Building and maintaining scalable APIs and event-driven architectures Writing clean, maintainable, and well-tested code using Node.js, TypeScript, and JavaScript … including Terraform, AWS CDK, or CloudFormation Experience building and maintaining CI/CD pipelines Knowledge of AWS services such as Lambda, DynamoDB, IAM, and S3 Understanding of cloud security best practices and secure application design Experience working within Agile software delivery environments AWS certifications such as Solutions Architect, Developer ...

testing, preferably using Cucumber CI/CD experience (GitLab, Jenkins or GitHub Actions) Agile delivery experience (Scrum/Kanban) Desirable Skills AWS services (SQS, S3, SNS and/or KMS) GitLab CI/CD Gatling or K6 load testing Kubernetes or Amazon ECS Senior-Level Experience Experience ...

creating a world of work where potential matters more than experience. Our market-leading, task-based psychometric assessments help organisations like Amazon, Siemens and Jet2 make fair, evidence-based hiring decisions. We’ve doubled ARR year-on-year for the past three years and are looking … Python Http4s, Http4k, Circe, Cats, Cats-Effect, Doobie, React, Exposed Testing Specs2, ScalaCheck Infrastructure & DevOps AWS (EKS, Lambda, RDS/Postgres, DynamoDB, SQS, Kinesis, S3, Cognito, Route53, VPC, EC2) Terraform, Kubernetes, Helm, Ansible, Puppet GitLab CI Observability & Data Prometheus, Grafana, OpenSearch Snowflake You don’t need experience in every ...

Lake, and Databricks notebooks. Develop end-to-end ETL/ELT pipelines for ingestion, transformation, validation, and consumption. Work with AWS services such as S3, Glue, Lambda, EMR, IAM, KMS, CloudWatch, Secrets Manager, Athena, and related services. Implement lakehouse architecture using Databricks, Delta Lake, and AWS S3. Build data … optimization. Experience with Spark SQL and large-scale distributed data processing. Strong understanding of Delta Lake and lakehouse architecture. Hands-on experience with AWS S3 as a data lake storage layer. Experience in building ETL/ELT pipelines for batch and near-real-time data processing. Experience with data ...

Lead, coach and develop a small team of Data & AI Engineers. Set technical direction, engineering standards and best practice. Evolve our AWS, Snowflake, S3 and PostgreSQL platform into a modern, AI-ready data ecosystem. Build scalable data acquisition and ingestion pipelines across multiple internal and external data sources. Develop … technologies Snowflake or similar cloud data platforms PostgreSQL and modern data architectures Data orchestration tools such as Airflow, Prefect or similar Amazon S3 Event-driven architectures and distributed systems Building scalable engineering solutions using APIs and multiple data sources You'll understand that great AI starts with ...

focus on improving production services and incident response. \n AWS Cloud Services leadership: Advanced hands-on experience designing and deploying scalable systems utilizing Amazon Web Services, including DynamoDB, SNS, SQS, and S3. \n AI-Assisted Development: You are highly comfortable leveraging AI coding assistants and LLMs to accelerate ...

strong focus on improving production services and incident response. AWS Cloud Services leadership: Advanced hands-on experience designing and deploying scalable systems utilizing Amazon Web Services, including DynamoDB, SNS, SQS, and S3. AI-Assisted Development: You are highly comfortable leveraging AI coding assistants and LLMs to accelerate workflow ...

strong focus on improving production services and incident response. AWS Cloud Services leadership: Advanced hands-on experience designing and deploying scalable systems utilizing Amazon Web Services, including DynamoDB, SNS, SQS, and S3. AI-Assisted Development: You are highly comfortable leveraging AI coding assistants and LLMs to accelerate workflow ...

strong focus on improving production services and incident response. \ NAWS Cloud Services leadership: Advanced hands-on experience designing and deploying scalable systems utilizing Amazon Web Services, including DynamoDB, SNS, SQS, and S3. \ NAI-Assisted Development: You are highly comfortable leveraging AI coding assistants and LLMs to accelerate workflow ...

accelerate your daily workflow, from scaffolding code and writing tests to debugging complex issues. \n AWS Cloud Services: Hands-on experience with specific Amazon Web Services, including DynamoDB, SNS, SQS, and S3. \n Bonus points: Previous experience working in an international company or dealing with high-volume transactional ...

LLMs to accelerate your daily workflow, from scaffolding code and writing tests to debugging complex issues.AWS Cloud Services: Hands-on experience with specific Amazon Web Services, including DynamoDB, SNS, SQS, and S3.Bonus points: Previous experience working in an international company or dealing with high-volume transactional systems (like ...

accelerate your daily workflow, from scaffolding code and writing tests to debugging complex issues. AWS Cloud Services: Hands-on experience with specific Amazon Web Services, including DynamoDB, SNS, SQS, and S3. Bonus points: Previous experience working in an international company or dealing with high-volume transactional systems (like ...