7 of 7 Amazon Redshift Jobs in Scotland

delivering enterprise data warehousing and lakehouse solutions on Snowflake, including migrations from legacy EDW (Teradata, Oracle, SQL Server, etc.) and modern platforms (BigQuery, Redshift, Synapse, etc.).Deep data modeling expertise (dimensional, Data Vault, 3NF) and semantic design, including Snowflake semantic views and Horizon Context.Strong ELT/ETL and orchestration ...

/CD and other DevOps practices such as IaC Testing Additional experience with the following would be beneficial but not essential: Data Warehousing (Snowflake, Redshift, Synapse, BigQuery, etc.) Relational, NoSQL, graph and vector databases Streaming technologies (Kafka, Kinesis, Flink, etc.) Containers and related services (Docker, Kubernetes, container Registries ...

. Data Integration Tools: Knowledge of platforms like Airflow, Apache NiFi, or Talend. Data Storage and Modelling: Experience with data warehousing tools (e.g. Snowflake, Redshift, BigQuery) and schema design. Version Control and CI/CD: Familiarity with Git, Docker, and CI/CD pipelines for deployment. Experience: 5+ years ...

server) Data Integration Tools: Knowledge of platforms like Airflow, Apache NiFi, or Talend. Data Storage and Modelling: Experience with data warehousing tools (e.g. Snowflake, Redshift, BigQuery) and schema design. Version Control and CI/CD: Familiarity with Git, Docker, and CI/CD pipelines for deployment. Experience 2+ years ...

data lakehouse architectures using Delta Lake, Apache Spark, or similar open-source frameworks Familiarity with AWS-native data services such as Glue, Lake Formation, Redshift, or Athena Exposure to data governance practices including cataloging, lineage tracking, and data access control at the platform layer AWS certification(s) in cloud ...

The Data Architect is responsible for designing, building, and managing the data warehouse’s data architecture, ensuring it is scalable, secure, and optimized for performance. This position plays a crucial role in shaping our data ...

maintain the batch and ELT pipelines the ML work sits on, using Python, PySpark, and cloud data services (e.g., AWS Glue, EMR, S3, Redshift, Athena, or the Databricks/Snowflake equivalents), making sound decisions on architecture, data modelling, and tooling and weighing up trade-offs in performance, cost … need to be the person designing the model Have designed and operated production data pipelines on a modern cloud data platform, AWS (Glue, EMR, Redshift, S3/Lake Formation), Databricks, Snowflake or comparable, and can talk about which of those decisions would travel to a different one, and which ...