1 to 25 of 115 Permanent Amazon Redshift Jobs in the UK excluding London

engineering role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field ● Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Redshift, BigQuery or other big data solutions ● Experience in data modelling and tools such as dbt, ETL processes, and data warehousing ● Experience with at least one of the programming languages More ❯

engineering role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field ● Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Redshift, BigQuery or other big data solutions ● Experience in data modelling and tools such as dbt, ETL processes, and data warehousing ● Experience with at least one of the programming languages More ❯

to minimise disruption. Collaborate with various teams to align migration processes with organisational goals and regulatory standards. Proficiency in AWS ETL technologies, including Glue, Data Sync, DMS, Step Functions, Redshift, DynamoDB, Athena, Lambda, RDS, EC2 and S3 Datalake, CloudWatch for building and optimizing ETL pipelines and data migration workflows. Working knowledge of Azure data engineering tools, including ADF (Azure More ❯

to minimise disruption. Collaborate with various teams to align migration processes with organisational goals and regulatory standards. Proficiency in AWS ETL technologies, including Glue, Data Sync, DMS, Step Functions, Redshift, DynamoDB, Athena, Lambda, RDS, EC2 and S3 Datalake, CloudWatch for building and optimizing ETL pipelines and data migration workflows. Working knowledge of Azure data engineering tools, including ADF (Azure More ❯

to minimise disruption. Collaborate with various teams to align migration processes with organisational goals and regulatory standards. Proficiency in AWS ETL technologies, including Glue, Data Sync, DMS, Step Functions, Redshift, DynamoDB, Athena, Lambda, RDS, EC2 and S3 Datalake, CloudWatch for building and optimizing ETL pipelines and data migration workflows. Working knowledge of Azure data engineering tools, including ADF (Azure More ❯

introduction of streaming and real-time data processing alongside traditional batch systems. Mentoring junior engineers and sharing best practices to strengthen data engineering capability. Tech Stack & Environment AWS ecosystem: Redshift, S3, Glue, Lambda, Step Functions, CloudFormation Core tools: Python, SQL, DBT, Terraform, GitHub, CI/CD Data warehousing: 600TB+ environment with expansion into Databricks BI & analytics: Power BI, Tableau More ❯

environments. Relevant Skills: Essential Skills: Proficiency in Python or Scala for data processing Strong SQL skills for querying and managing relational databases Experience with AWS services including S3, Glue, Redshift, Lambda, and Athena Knowledge of ETL processes and data pipeline development Understanding of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience More ❯

environments. Relevant Skills: Essential Skills: Proficiency in Python or Scala for data processing Strong SQL skills for querying and managing relational databases Experience with AWS services including S3, Glue, Redshift, Lambda, and Athena Knowledge of ETL processes and data pipeline development Understanding of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience More ❯

engineers and support their growth. Implement best practices for data security and compliance. Collaborate with stakeholders and external partners. Skills & Experience: Strong experience with AWS data technologies (e.g., S3, Redshift, Lambda). Proficient in Python, Apache Spark, and SQL. Experience in data warehouse design and data migration projects. Cloud data platform development and deployment. Expertise across data warehouse and More ❯

Requirements Proven experience as a Data Engineer, with a track record of designing and managing scalable data pipelines and infrastructure in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages More ❯

using a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience More ❯

team of highly technically skilled engineers, who are enhancing Creditsafe's data offerings with high throughput and scalability as primary goals. The data delivery platform is built upon AWS Redshift and S3 cloud storage. The platform manages billions of objects, with daily increments in the 10s of millions. Our ETL processes are built in Python and Rust, efficiently transforming More ❯

using a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience More ❯

using a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience More ❯

and big data platforms. Knowledge of data modeling, replication, and query optimization. Hands-on experience with SQL and NoSQL databases is desirable. Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: Comfortable operating in hybrid environments (cloud and on-prem). Experience integrating diverse data sources and systems. Understanding of secure data transfer More ❯

development projects, data modelling, and cloud data platform deployments. Mentor data engineers and contribute to best practices across the team. Key skills: Strong experience with AWS data services (S3, Redshift, Glue, Lambda, Lake Formation, CloudFormation). Proficiency in SQL, Python (Pandas), Spark or Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild More ❯

cloud technologies for ETL pipeline, data 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 Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem More ❯

cloud technologies for ETL pipeline, data 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 Work to agile best practices and cross-functionally with multiple teams and stakeholders. You ll be using your technical skills to problem More ❯

cloud technologies for ETL pipeline, data 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 Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem More ❯

cloud technologies for ETL pipeline, data 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 Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem More ❯

Key Skills & Experience: Proven experience as a Senior Data Engineer in a large-scale or complex environment. Strong hands-on expertise with AWS data services (e.g., S3, Glue, Lambda, Redshift, Athena, EMR). Experience building data lakes and modern data platforms from the ground up. Proficiency with Python, SQL, and orchestration tools such as Airflow or dbt. Strong understanding More ❯

of data in logistics, this is the role for you. What You'll Be DoingData Platform & BI Engineering Architect and implement cloud-native data platforms (AWS S3, Glue, Athena, Redshift, QuickSight). Build reliable, governed data pipelines with CI/CD and infrastructure as code. Design dimensional models and deliver robust SQL/Python transformations. Systems Integration & Application Support More ❯

Governance, Security & Compliance - aligned to Data best practices. Liaison with IT Business Systems & Business Teams & Third Parties. Drive Continuous Improvement. Technical Skills Required: Azure Data Factory. AWS Data Services (Redshift, S3, Lambda) - Desirable. SSRS - hands-on experience. ETL - Design, Data Quality Frameworks & Pipeline Management. SQL - Star Schema - Data Modelling. Data Warehouse Design, Development & Testing. Data Warehousing Methodologies. User Support More ❯

or analytics engineering, ideally within fintech, SaaS, or digital platforms Deep proficiency in SQL and hands-on experience with dbt Experience working with modern data warehouses (Snowflake, BigQuery, or Redshift) Familiarity with software engineering principles (Git, CI/CD, testing frameworks) Strong understanding of data visualisation and BI tools Confident communicator able to translate technical detail into clear business More ❯

or analytics engineering, ideally within fintech, SaaS, or digital platforms Deep proficiency in SQL and hands-on experience with dbt Experience working with modern data warehouses (Snowflake, BigQuery, or Redshift) Familiarity with software engineering principles (Git, CI/CD, testing frameworks) Strong understanding of data visualisation and BI tools Confident communicator able to translate technical detail into clear business More ❯