24 of 24 Amazon Kinesis Jobs in the North of England

live services, and play a key role in resolving complex production issues.Stay up to date with the latest technologies and AWS services, including Amazon Bedrock and Amazon Q Business, to enhance client capabilities and foster innovation.Actively contribute to the engineering community.Contribute to technical pre-sales activity, including … maintaining cloud-based platforms and infrastructure, with a focus on AWS.Hands on experience with AWS, including practical delivery across core services such as Amazon EC2, Amazon EKS, Amazon RDS, Amazon Redshift, Amazon S3, Amazon VPC, AWS Identity and Access Management (IAM), AWS Lambda ...

including data pipelines, ETL/ELT processes, and data integration frameworks. Develop andoptimizedata architectures using AWS services such as S3, Glue, Lambda, Redshift, Kinesis, EMR, Amazon OpenSearch Service, and graph databases such as Amazon Neptune, and related technologies. Ensure solutions follow AWS best practices for security, performance … llbring Considerable experiencein data engineeringfocused on AWS data platforms and services. Strong hands-on experience withAWS data servicesincluding S3, Glue, Lambda, Redshift, Athena, EMR, Kinesis, Amazon OpenSearch Service, and graph databases such as Amazon Neptune, and related technologies. Proficiencyin programming languages such asPythonandSQL fordata processing and transformation. ...

Develop and support real‐time streaming pipelines and event‐driven integrations. Integrate data from multiple sources (streaming, batch, APIs) using AWS managed services (e.g., Kinesis, MSK, Lambda, Glue). Data Architecture & Standards Contribute to data modelling, data architecture best practices, and modern patterns (e.g., medallion architecture). Ensure data ...

principles including Zero Trust, identity-first security, secrets management, and network segmentation. Desirable Experience Experience with Cribl and security data pipeline management. Knowledge of Kinesis, Amazon S3, Amazon Security Lake, or similar technologies. Understanding of OCSF and security data normalisation. Experience working within government, defence, highly regulated ...

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/ ...

cloud platforms using services such as object storage (e.g., S3, ADLS, GCS), cloud data warehouses (e.g., Snowflake, BigQuery, Synapse Analytics), streaming services (e.g., Kinesis, Event Hubs, Pub/Sub), and security services (e.g., KMS, KeyVault), with a focus on architectural governance.Developing logical and physical data models for NoSQL data ...

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 ...

unstructured data) Proficiency with Parquet/Delta Lake or other modern data storage formats Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines Experience processing ...

robust data quality, validation, reconciliation, and audit controls across betting, trading, and customer data domains. Develop streaming and micro-batch data solutions using AWS Kinesis, Apache Kafka, or Amazon MSK to support real-time sportsbook and in-play data feeds. Build and maintain data solutions using AWS services … uptime You're strong on AWS data engineering AWS is your primary cloud — you're confident across Glue, Lambda, Athena, S3, Redshift, RDS, Kinesis, MSK, and Step Functions You've built real-time or near-real-time pipelines using streaming frameworks — Kinesis Data Streams, Kafka, Flink, or Spark ...

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 ...

edge, Databricks Mosaic AI, Vector Search and Unity Catalog, or Azure OpenAI, Azure AI Foundry and Azure AI Search. AWS: Glue, Lambda, Step Functions, Kinesis, EMR, Athena, Redshift, S3 data lakes; and, for the AI edge, Amazon Bedrock, Knowledge Bases for Bedrock About Capgemini Hybrid working: The places ...

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 ...

production deployment and optimisation Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams Partner with customers to translate business challenges … career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that ...

production deployment and optimisation 2. Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker 3. Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams 4. Partner with customers … experience in a professional field or military Experience as technical specialist in design and architecture Experience in database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) Experience in consulting, design and implementation of serverless distributed solutions Experience in software development with object oriented language Experience in cloud based solution ...

fluent across the core services, for example: Storage & Lakehouse: RDS, DynamoDB, S3, SageMaker Lakehouse Processing & ETL: Glue, EMR, Athena, CDC/DMS, DataBrew, Kinesis, dbt Data management & metadata: Lake Formation, Glue Data Catalog, SageMaker Catalog/DataZone AI: Bedrock (including AgentCore) and SageMaker AI On Azure, you’re fluent … analytics and decision‐making. AI : You understand how AI is built and deployed in modern data platforms (Databricks, Snowflake) and cloud‐native services like Amazon Bedrock, with enough depth to guide teams and advise clients, spanning LLMs and SLMs, agentic automation, Human in the Loop and MLOps. Data Architecture ...

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 ...

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 ...

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 ...