1 to 25 of 159 Amazon Redshift Jobs in the UK

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 ❯

or similar Cloud data ecosystem (AWS) : hands-on experience with core AWS data services. Key services include: S3 for data lake storage AWS Glue for ETL and data cataloging Amazon Redshift or Athena for data warehousing and analytics Lambda for event-driven data processing. ETL/ELT pipeline development : experience in designing, building, and maintaining robust, automated data More ❯

or similar Cloud data ecosystem (AWS) : hands-on experience with core AWS data services. Key services include: S3 for data lake storage AWS Glue for ETL and data cataloging Amazon Redshift or Athena for data warehousing and analytics Lambda for event-driven data processing. ETL/ELT pipeline development : experience in designing, building, and maintaining robust, automated data 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 ❯

major cloud platforms such as Azure, AWS, or GCP . Exposure to tools such as Matillion, Fivetran, dbt, or Snowflake . Familiarity with modern data warehouse environments (e.g. BigQuery, Redshift, Databricks ). Knowledge of Python or other scripting languages for automation. Interest in AI and its growing role within data engineering. Previous experience in software engineering or integration. Location More ❯

solutions. Support and mentor junior engineers, contributing to knowledge sharing across the team. What We're Looking For Strong hands-on experience across AWS Glue, Lambda, Step Functions, RDS, Redshift, and Boto3. Proficient in one of Python, Scala or Java, with strong experience in Big Data technologies such as: Spark, Hadoop etc. Practical knowledge of building Real Time event 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 ❯

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 ❯

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 ❯

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 ❯

AWS (preferred) or Azure , and experience managing data pipelines in the cloud. Strong skills in Python and SQL , with a solid grasp of data warehousing concepts. Experience with DBT , Redshift , or Postgres , and familiarity with BI tools (Power BI preferred). Proven understanding of CI/CD principles , DevOps, and infrastructure automation. Excellent communication skills - able to collaborate across 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 ❯

Familiarity with ETL tools and big data platforms. Knowledge of data modelling, replication, and query optimization. Experience with SQL and NoSQL databases. Exposure to data warehousing tools (e.g., Snowflake, Redshift, BigQuery). Data Platform Management Experience in hybrid environments (cloud/on-prem). Skilled in integrating diverse data sources. Understanding of secure data transfer and disaster recovery planning. More ❯

Engineering with strong Python and SQL skills. Background in building and maintaining ETL/ELT pipelines in a cloud environment (AWS or Azure). Knowledge of data warehousing (e.g., Redshift, Postgres) and tools like DBT . Familiarity with CI/CD , data modelling, and Agile practices. Comfortable collaborating with Data Scientists and translating business needs into technical solutions. Experience 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 ❯