26 to 34 of 34 Amazon Kinesis Jobs in the UK excluding London

design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis, DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB), GraphQL and modern data warehouse tools including Snowflake and DataBricksAbility to think strategically and relate architectural decisions ...

detail and problem-solving skills.Desirable Skills:Real-time systems/telemetry dashboards;IoT platforms;Robotics or autonomous system integration;Geospatial/mapping tools.Data streaming (Kinesis, Kafka)What we OfferWork life balance promoted with every other Friday off;30 days annual leave;Competitive rate of pay, reviewed annually;Enhanced Company ...

scripting/programming language (Python, Go, or similar) for building security automation and tooling. Experience with detection engineering, creating and managing data streams (Cribl, Kinesis) and SIEM tooling (Splunk, QRadar, Sentinel, ArcSight) , or building alerting/observability for security events from across an enterprise. Experience setting up segregated ...

serve large datasets. Work extensively with S3 (Hive-partitioned Parquet data lake), Athena for SQL querying and analysis, DynamoDB for low-latency caching, and Kinesis/SQS for streaming and queue-based integration — including customer-facing "bring your own stream" pipelines.Develop robust RESTful APIs and services (FastAPI) that expose … Engineer on large, production software applications.Strong Python engineering skills, including dependency and environment management with Poetry.Hands-on experience with AWS, particularly S3, Athena, DynamoDB, Kinesis, SQS, ECS, and CloudWatch.Experience building RESTful APIs and services with FastAPI.Hands-on experience with Infrastructure as code with Terraform.Containerisation with Docker.Data-engineering fundamentals: working ...

serve large datasets. Work extensively with S3 (Hive-partitioned Parquet data lake), Athena for SQL querying and analysis, DynamoDB for low-latency caching, and Kinesis/SQS for streaming and queue-based integration — including customer-facing "bring your own stream" pipelines. Develop robust RESTful APIs and services (FastAPI) that … large, production software applications. Strong Python engineering skills, including dependency and environment management with Poetry. Hands-on experience with AWS, particularly S3, Athena, DynamoDB, Kinesis, SQS, ECS, and CloudWatch. Experience building RESTful APIs and services with FastAPI.Hands-on experience with Infrastructure as code with Terraform. Containerisation with Docker. Data ...

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 ...

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 ...