16 of 16 Permanent Amazon Kinesis Jobs in the UK excluding London

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/ ...

scalable data pipelines using Java (primary) and technologies like Kafka, Flink, or SparkDeveloping 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 platformsDeploying and maintaining solutions using CI/CD and Infrastructure ...

considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectationsPreferred qualificationsExperience with streaming (Structured Streaming, Kafka/Event Hubs/Kinesis).Experience implementing data quality frameworks (Great Expectations, DQ) and data testing in CI.Exposure to Unity Catalog (or similar) for governance and fine-grained permissions.J.P. ...

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 ð Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using ...

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 ð Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using ...

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 ...

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 ...

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 ...

dataHave exposure to 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)Have experience with DataOps conceptsWhy join AND Digital We’re building a culture where talented people can do meaningful work ...

end.Technical Proficiency: Strong experience with Python for building backend services and data pipelines. Familiarity with AWS services (e.g. S3, RDS/Postgres, Kinesis, ECS, Lambda) and infrastructure tooling (Terraform).Data Ingestion: Experience designing pipelines that handle varied, schema-evolving, high-volume payloads reliably and at scale — including robust error ...

design & distributed processing through technologies such as Apache Spark or Databricks/Snowflake is a huge plusKnowledge on messaging technologies like Kafka/AWS Kinesis or similar is a plusOur Values Act Like an Owner - Think and operate with intention, purpose and care. Own outcomes.Build Together - Collaborate to unlock ...

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 ...

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 ...

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 ...