16 of 16 Permanent Amazon Redshift Jobs in Shrewsbury

experience deploying highly available cloud services (AWS or Azure) Proficiency with IaC tools: Terraform, CloudFormation (or Bicep) Experience with cloud database technologies (e.g., Snowflake, Redshift) Familiarity with Linux and containerisation (Docker) Exposure to data platform/data science tooling (dbt, Airflow, etc.) Solid understanding of networking concepts and protocols More ❯

not? We’ll help you get there: Understanding of cloud computing security concepts Experience in relational cloud-based database technologies like Snowflake, BigQuery or Redshift Experience in open-source technologies like Spark, Kafka, Beam understanding of Cloud tools such as AWS, Microsoft Azure or Google Cloud Familiarity with DBT More ❯

of Spark and Airflow - Experience in designing data pipelines using cloud-native services on AWS - Extensive knowledge of AWS services, including API Gateway, Lambda, Redshift, Glue, CloudWatch, etc. - Experience in deploying AWS resources using Terraform - Hands-on experience in setting up CI/CD workflows using GitHub Actions **Eligibility More ❯

Responsibilities develop, and maintain ETL/ELT data pipelines using AWS services Data, Databricks and dbt Manage and optimize data storage solutions such as Amazon S3, Redshift, RDS, and DynamoDB. Implement and manage infrastructure-as-code (IaC) using tools like Terraform or AWS CloudFormation. Monitor and optimize the More ❯

AWS. Collaborate with engineering teams to ensure a smooth transition and system stability. Languages & Scripting: Python (primary scripting language for Lambda functions) SQL (BigQuery, Redshift) R (not essential but beneficial for interpreting existing scripts) Cloud & Infrastructure: AWS services including Lambda, API Gateway, S3, CloudWatch, Kinesis Firehose Terraform for infrastructure More ❯

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 ❯

including Hugging Face Transformers and other pre-trained architectures. Build, train, and evaluate ML models using services such as AWS SageMaker, Bedrock, Glue, Athena, Redshift, and RDS. Develop and expose secure APIs using Apigee, enabling easy access to AI functionality across the Manage the entire ML lifecycle—from training More ❯

environment is a strong advantage. Preferred Skills (Nice to Have) Data literacy (e.g., SQL, Tableau, Power BI, R, Smartsheet, Adobe Analytics, Google Analytics, AWS Redshift/Timestream). Experience in production engineering. Knowledge of SaaS tools, endpoint management, identity governance, or content management systems 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 ❯

using data to support health research and services that positively impact lives. Key Responsibilities: Lead the architecture and delivery of scalable data platforms using Amazon Web Services (AWS) . Build and maintain end-to-end data pipelines and support the team in adopting CI/CD practices. Leverage AWS … tools such as S3 , Glue , Redshift , and Lambda to process and analyse data efficiently. Use scripting languages such as Python , Bash , or R to automate workflows and develop data solutions. Implement version control through Git and GitHub , and contribute to a collaborative development environment. Manage a wide range of More ❯

platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability … Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Desirable Skills Designing Databricks based solutions for 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 ❯

Job Title: Data Engineering Manager Job Type: Full Time, Permanent Location: London, Hybrid Role Purpose At Travelex we are developing modern data technology and data products. Data is central to the way we define and sell our foreign currency exchange More ❯