10 of 10 Amazon Redshift Jobs in the North of England

environment, contributing to technical discussions and problem-solving initiatives. Senior Data Engineer Requirements: Proven experience in building and managing cloud-based data platforms (AWS Redshift/Glue, Azure Data Factory/Synapse, Google BigQuery/Dataflow). Strong programming skills in Python, SQL, and Java for data engineering tasks. ...

following are nice to have: Data Engineering & Programming: • Python • SQL • Spark/PySpark • Scala • Data modelling and warehousing concepts Cloud & Platforms: • AWS (S3, Redshift, Glue, EMR, Lambda) • Other cloud platforms (Azure/GCP considered) • Data lake and data warehouse architectures General: • Strong problem-solving skills • Experience working in agile ...

communities and quality forums Key Skills Strong experience designing and delivering scalable data engineering solutions Expertise in cloud-based data platforms such as AWS (Redshift, Glue), Azure (Data Factory, Synapse) or GCP (BigQuery, Dataflow) Advanced proficiency in SQL, including optimisation and performance tuning Strong experience with ETL/ ...

experience: Strong Python and SQL skills AWS or GCP (NOT Azure) Orchestration, ideally with Airflow or Dagsta but open to others Data warehousing - Snowflake, Redshift, BigQuery (NOT Databricks) Terraform BENEFITS The successful Senior Data Engineer will receive the following benefits: Salary between £80,000 - £100,000 - depending on experience ...

implementing enterprise-scale data solutions Deep expertise in data modelling techniques with strong SQL proficiency Good knowledge of cloud data platforms (AWS preferred: Redshift, Athena, S3, Glue, knowledge of Azure or GCP beneficial) and modern data engineering patterns including ETL/ELT Experience with data governance frameworks, data quality ...

Strong foundations in mathematics and analytical reasoning Strong hands-on experience with, programming & Analytics: Python, SQL, Scikit-learn, TensorFlow Data & Cloud: AWS (Athena, S3, Redshift), data warehousing, ETL pipelines Visualisation & Tools: Jupyter, Visual Studio Code, Microsoft Excel, dashboards and reporting solutions Development Environments: Linux/Ubuntu, Git/Bitbucket ...

data warehousing principles Expertise in data and metadata management Thorough understanding of security standards and controls Experience working with cloud data warehouse technologies, ideally Amazon Redshift, Advanced SQL skills Experience in these areas would be helpful: Experience of Jira Version Control (GitHub) Experience with ABI tools (preferably Power ...

/Studio, PowerDesigner, etc.) Experience with major database platforms (e.g. SQL Server, Oracle, Azure Data Lake, Hadoop, Azure Synapse/SQL Data Warehouse, Snowflake, Redshift etc. ...

ground running in this role, you will have proven experience designing, building and maintaining enterprise-scale Data Lakes and Data Warehouses on Amazon Redshift. As a Data Engineer, you will turn complex data into clarity, build scalable solutions, and help deliver insights that transform how the organisations clients work. … service + many more. Responsibilities: Convert raw data into trusted analytical assets and bring insight to life through Power BI. Build and maintain the Redshift-based Enterprise Data Warehouse and S3 Data Lake. Develop and optimise ELT/ETL pipelines across diverse data sources. Develop Power BI datasets, dashboards ...

pipelines on AWS Building and maintaining ML ready datasets to support model training, inference, and experimentation Improving data warehouse design and performance within AWS Redshift, including refactoring poorly structured data Integrating new and underused data sources to unlock additional value Supporting feature store development and data pipelines … Experience Strong commercial experience building production grade data pipelines using Python and SQL Hands on experience with AWS data services such as S3, Redshift, Glue, Athena, and streaming technologies like Kinesis Experience working with large scale, high velocity event data and understanding the trade offs around cost, performance ...