9 of 9 Remote/Hybrid Permanent Amazon Kinesis Jobs

cloud platform:Azure (Synapse, Data Factory, Databricks)AWS (S3, Glue, Redshift, Lambda)GCP (BigQuery, Dataflow)Data Platform ExpertiseExperience with:Data warehousing solutionsStreaming technologies (Kafka, Kinesis, Pub/Sub)Familiarity with DevOps/DataOps practicesCI/CD pipelinesInfrastructure as Code (Terraform, ARM, CloudFormation)About NTT DATANTT DATA ...

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/ ...

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 ...

Lake, Unity Catalog, and streaming technologies.Broad cloud expertise across Azure (Synapse, ADF, Event Hub, ADLS Gen2, Purview, Key Vault) and AWS (S3, Glue, EMR, Kinesis, Athena, Lake Formation, IAM), with strong multi-cloud experience.Strong understanding of modern engineering practices, including CI/CD for data platforms, automated deployment pipelines ...

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 ...

pipelines with a focus on data integrity Experience with multiple data storage technologies (MySQL, Hadoop, Cassandra) Experience with AWS (DynamoDB, RDS, Step functions, EC2, Kinesis) is a plus. Experience with unit, integration, and end-to-end testing paradigms Experience with defining and upholding SLOs/KPIs and participating ...

least 2 years in a customer-facing, embedded, or solutions engineering capacityStrong hands-on experience with streaming and event-driven architectures — Kafka, Flink, Kinesis, Spark Streaming, or equivalent (DynamoDB and MemoryDB/Redis)AWS Cloud Fluency - understand how to design scalable end-to-end architectures and pipelines on large … volumes of data (think Kafka/Flink for streaming + AWS Lambda + Kinesis)Solid data engineering fundamentals: pipeline design, SQL, Python, schema modeling, data qualityExperience building or integrating with CDP, marketing automation, or behavioral data-management platformsProven ability to go from ambiguous problem to working system ...