6 of 6 Permanent Amazon Redshift Jobs in Dorset

large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake, Databricks, Redshift, BigQuery) Familiarity with data pipelines and orchestration tools like Airflow Work closely with Data Engineers to ensure model-ready data and scalable pipelines. Nice More ❯

ideal candidate would have 10+ years experience in Data Engineering/Architecture and have good knowledge within: Cloud (AWS, GCP, Azure) Data Warehousing (Snowflake, Redshift, BigQuery) ETL (Data Fabric, Data Mesh) DevOps (IaC, CI/CD, Containers) Leadership/Line Management Consulting/Client Facing Experience In return they More ❯

assist with the continued scaling and optimisation of these. Their ideal candidate would have good knowledge within: Cloud (AWS, GCP, Azure) Data Warehousing (Snowflake, Redshift, BigQuery) ETL (Data Fabric, Data Mesh) DevOps (IaC, CI/CD, Containers) Consulting/Client Facing Experience In return they would be offering Free More ❯

drive customer loyalty? Expect to deep dive into customer segmentation, lifetime value, cohort behaviour , and funnel performance -all powered by a strong modern stack: Redshift, SQL, Python, and Looker . You'll thrive in this role if you: Love solving business problems with data Have strong SQL and some More ❯

primary, secondary, and tertiary sources. Cloud, Infrastructure, and Platform Engineering: Develop and deploy data workflows on AWS or GCP , using services such as S3, Redshift, Pub/Sub, or BigQuery. Containerize data processing tasks using Docker , orchestrate with Kubernetes , and ensure production-grade deployment. Collaborate with platform teams to … ensure scalability, resilience, and observability of data pipelines. Database Engineering : Write and optimize complex SQL queries on relational (Redshift, PostgreSQL) and NoSQL (MongoDB) databases. Work with ELK stack (Elasticsearch, Logstash, Kibana) for search, logging, and real-time analytics. Support Lakehouse architectures and hybrid data storage models for unified access More ❯

our large-scale AI models. Key Responsibilities: • Architect, design, and manage scalable data pipelines and infrastructure across on-premise and cloud environments (AWS S3, Redshift, Glue, Step Functions). • Ingest, clean, wrangle, and preprocess large, diverse, and often messy datasets—including structured, unstructured, and geospatial data. • Collaborate with ML … architecture, or similar roles. • Expert proficiency in Python, including popular data libraries (Pandas, PySpark, NumPy, etc.). • Strong experience with AWS services—specifically S3, Redshift, Glue (Athena a plus). • Solid understanding of applied statistics. • Hands-on experience with large-scale datasets and distributed systems. • Experience working across hybrid More ❯