51 to 60 of 60 Amazon Kinesis Jobs in the UK excluding London

Shores, we're 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 … your path has been unconventional, we'd love to hear from you. Our Stack Infrastructure & DevOps AWS (EKS, Lambda, RDS/Postgres, DynamoDB, SQS, Kinesis, S3, Cognito, Route53, VPC, EC2) Terraform, Kubernetes, Helm, Ansible, Puppet GitLab CI Observability & Security Prometheus, Grafana, OpenSearch, CloudWatch Okta (SSO/IdP) Vulnerability management ...

Amazon Development Centre (London) Limited We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to help build industry‐leading language technology powering Rufus, our AI‐driven search and shopping assistant, helping customers with their shopping tasks at every step … particular those based on large language models, information retrieval, recommender systems and knowledge graphs, to be tailored to customer needs. You will handle Amazon‐scale use cases with significant impact on our customers' experiences. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will ...

Software Engineering, Agentic & AI Development (30%): Solid software engineer principles (pipelines, toolsets, testing, linting, vulnerability scanning, etc.) Production‐level experience with tools such as Amazon Bedrock, AWS AgentCore, Azure AI Studio, LangChain, and writing automation scripts or custom AI agents using node or python. Data Engineering (30%): Experience deploying … maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability tooling (OpenTelemetry) alongside automated cost‐control systems (such as Karpenter, Infracost, OpenCost, or Cloud Custodian). Domain & Sector ...

Software Engineering, Agentic & AI Development (30%): Solid software engineer principles (pipelines, toolsets, testing, linting, vulnerability scanning, etc.) Production‐level experience with tools such as Amazon Bedrock, AWS AgentCore, Azure AI Studio, LangChain, and writing automation scripts or custom AI agents using node or python. Data Engineering (30%): Experience deploying … maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability tooling (OpenTelemetry) alongside automated cost‐control systems (such as Karpenter, Infracost, OpenCost, or Cloud Custodian). Domain & Sector ...

Software Engineering, Agentic & AI Development (30%): Solid software engineer principles (pipelines, toolsets, testing, linting, vulnerability scanning, etc.) Production‐level experience with tools such as Amazon Bedrock, AWS AgentCore, Azure AI Studio, LangChain, and writing automation scripts or custom AI agents using node or python. Data Engineering (30%): Experience deploying … maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability tooling (OpenTelemetry) alongside automated cost‐control systems (such as Karpenter, Infracost, OpenCost, or Cloud Custodian). Domain & Sector ...

Software Engineering, Agentic & AI Development (30%): Solid software engineer principles (pipelines, toolsets, testing, linting, vulnerability scanning, etc.) Production-level experience with tools such as Amazon Bedrock, AWS AgentCore, Azure AI Studio, LangChain, and writing automation scripts or custom AI agents using node or python. Data Engineering (30%): Experience deploying … maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real-time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability tooling (OpenTelemetry) alongside automated cost-control systems (such as Karpenter, Infracost, OpenCost, or Cloud Custodian). Domain & Sector ...

primary focus on the Delta Lakehouse Platform on Databricks.Responsibilities:Data Ingestion: Build and optimize data ingestion pipelines using AWS services such as Lambda, Kinesis, and Glue.Data Transformation: Develop, maintain, and optimize transformation pipelines within our Delta Lake on Databricks.Data Modelling: Design and implement efficient and reliable data models … data engineering field in general. Provide recommendations on the adoption of new tools and technologies.Requirements:AWS Services: Proficiency in AWS services like Lambda, Kinesis, and Glue.Databricks & Delta Lake: Hands-on experience with Databricks and Delta Lakehouse architectures.Programming: Proficient in Python, Scala, and SQL for data engineering tasks.ETL Processes: Demonstrated ...

your career on AWS this is one where that depth actually gets used. AWS across the board, including S3, Glue, Redshift, Lake Formation and Kinesis Databricks and Snowflake running on top of AWS Spark and distributed processing frameworks for large-scale data Streaming technologies such as Kinesis ...

solving, what decisions you made and why Based in the UK with the right to work here Desirable Experience with technologies such as Kafka, Kinesis, PostgreSQL or DynamoDB Practical experience using AI development tools Cursor, GitHub Copilot, Claude Code, LLM APIs, MCP-based tooling or agentic workflows to meaningfully … solving, what decisions you made and why Based in the UK with the right to work here Desirable Experience with technologies such as Kafka, Kinesis, PostgreSQL or DynamoDB Practical experience using AI development tools Cursor, GitHub Copilot, Claude Code, LLM APIs, MCP-based tooling or agentic workflows to meaningfully ...

your career on AWS this is one where that depth actually gets used. • AWS across the board, including S3, Glue, Redshift, Lake Formation and Kinesis • Databricks and Snowflake running on top of AWS • Spark and distributed processing frameworks for large-scale data • Streaming technologies such as Kinesis ...