24 of 24 Amazon Kinesis Jobs in the UK excluding London

Data Factory. Azure Data Engineer Associate and Databricks Certified Data Engineer Professional AWS Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR , Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS and AWS Step Functions. Programming Skills: Strong ...

with infrastructure as code (Terraform or CloudFormation) Right to work in the UK or Republic of Ireland Nice to have Experience with streaming data (Kinesis, Kafka or similar) Apache Airflow or similar orchestration tooling Exposure to dbt for transformation layer management WHY APPLY? Salary up to £75,000 depending ...

data pipelines using Java (primary) and technologies like Kafka, Flink, or Spark Developing real-time streaming solutions and event-driven architectures using AWS services (Kinesis, MSK, Lambda, Glue) Contributing to data architecture, modelling, and best practices across modern data platforms Deploying and maintaining solutions using CI/ ...

data pipelines using Java (primary) and technologies like Kafka, Flink, or Spark Developing real-time streaming solutions and event-driven architectures using AWS services (Kinesis, MSK, Lambda, Glue) Contributing to data architecture, modelling, and best practices across modern data platforms Deploying and maintaining solutions using CI/ ...

models Hands-on experience building and optimising ETL and ELT pipelines at scale Deep practical knowledge of AWS data services including Redshift, Glue, EMR, Kinesis and S3 Experience with modern data engineering tools such as dbt, Spark or Flink Proven experience with SQL and NoSQL databases including PostgreSQL, MySQL ...

warehouse and data lake design/building and data movement. AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders. You'll be using your ...

least one cloud data platform (e.g. Databricks, Snowflake, AWS, Azure or GCP) and experience of associated technologies (for example with AWS: DynamoDB, Redshift, Kinesis Pipelines, Glue, Lambda, QuickSight, etc) ideally including practical/hands-on experience of migration to or adoption of a cloud data platform. Strong Databricks expertise ...

data governance, quality, lineage, and security practices. Experience with real-time/streaming data technologies, data Ingestion/ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Experience in, or knowledge of, DevSecOps Tooling and Processes. Self-starter with the ability to appropriately prioritise and plan complex ...

hands-on experience of at least one cloud platform (AWS, Azure or GCP) and experience of associated technologies (for example with AWS: DynamoDB, Redshift, Kinesis Pipelines, Glue, Lambda, QuickSight, etc) Hands-on dataops experience (eg. CI/CD, version control, IaC, etc.) Have experience adopting a Data Product mindset ...

PostgreSQL, MySQL, DynamoDB and Bigtable Hands on experience building ETL/ELT pipelines and optimising data transformations Practical knowledge of AWS services such as Kinesis, S3 and Redshift, and GCP services such as Pub/Sub and BigQuery Experience with streaming technologies such as Kafka and real time processing ...

connecting enterprise API integrations, and implementing agentic guardrails. Data Engineering (30%): Practical experience implementing components of data pipelines, including real-time streaming tools (AWS Kinesis, Kafka), data orchestration (dbt, Airflow), and managing vector databases for RAG architectures. Observability & Cost Management: SRE/Platform experience with the practical application ...

connecting enterprise API integrations, and implementing agentic guardrails. Data Engineering (30%): Practical experience implementing components of data pipelines, including real-time streaming tools (AWS Kinesis, Kafka), data orchestration (dbt, Airflow), and managing vector databases for RAG architectures. Observability & Cost Management: SRE/Platform experience with the practical application ...

connecting enterprise API integrations, and implementing agentic guardrails. Data Engineering (30%): Practical experience implementing components of data pipelines, including real-time streaming tools (AWS Kinesis, Kafka), data orchestration (dbt, Airflow), and managing vector databases for RAG architectures. Observability & Cost Management: SRE/Platform experience with the practical application ...

connecting enterprise API integrations, and implementing agentic guardrails. Data Engineering (30%): Practical experience implementing components of data pipelines, including real-time streaming tools (AWS Kinesis, Kafka), data orchestration (dbt, Airflow), and managing Vector Databases for RAG architectures. Observability & Cost Management: SRE/Platform experience with the practical application ...

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 or emailing ...

that meet the requirements of the UK Gambling Commission and international licensing bodies Working with AWS services including S3, Glue, Lambda, Athena, Redshift, RDS, Kinesis, MSK, Lake Formation, Step Functions, and MWAA – selecting the right tool for each problem rather than defaulting to a stack Practice and people Mentoring … across the full data engineering stack – from ingestion and streaming through to warehousing, serving, and cost optimisation You have deep experience with streaming architectures – Kinesis, Kafka/MSK, Flink, or Spark Streaming – and know when each is the right choice You can model the cost implications of architecture decisions ...

that meet the requirements of the UK Gambling Commission and international licensing bodies Working with AWS services including S3, Glue, Lambda, Athena, Redshift, RDS, Kinesis, MSK, Lake Formation, Step Functions, and MWAA – selecting the right tool for each problem rather than defaulting to a stack Practice and people Mentoring … across the full data engineering stack – from ingestion and streaming through to warehousing, serving, and cost optimisation You have deep experience with streaming architectures – Kinesis, Kafka/MSK, Flink, or Spark Streaming – and know when each is the right choice You can model the cost implications of architecture decisions ...

closely with engineers across the platform. Essential Skills & Experience Strong commercial experience with Node.js and TypeScript Experience building APIs and microservices Experience with Kafka, Kinesis, or similar streaming technologies Strong understanding of event-driven architectures Hands-on AWS experience Experience with SQL and/or NoSQL databases Familiarity with ...

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 ...

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 … Typescript, 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 ...

edge environments, using platforms such as AWS or Azure, with a strong understanding of distributed systems and event‐driven architectures (e.g. Apache Kafka, AWS Kinesis, messaging and streaming patterns). Experience designing architectures for high volume, time critical, or sensor driven data, including streaming, time series, and geospatial data … senior leaders. Hands‐on experience with modern cloud native data platforms, such as: MODCloud – ICE, ACE environments AWS data services (e.g. S3, Redshift, EKS, Kinesis) Azure data services (e.g. Data Lake, Synapse, AKS) GCP Kubernetes‐based platforms and containerised data services Telicent Understanding of NATO data standards, interoperability requirements ...

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 ...