1 to 25 of 223 Amazon Redshift Jobs in the UK

Java Developer - Financial Technology - London/Hybrid (INSIDE IR35) (Key skills: Java, Spring Boot, Kubernetes, AWS EKS, Amazon Redshift, PostgreSQL, RESTful APIs, CI/CD, Microservices, iOS/Android Native, Agile, Financial Services) Are you a highly skilled Java Developer with a passion for building scalable, high-performance financial systems? Do you enjoy working with cutting-edge technologies … integrated with modern mobile and analytics platforms. As part of a collaborative, Agile development team, you will be responsible for building robust microservices, managing data pipelines across PostgreSQL and Amazon Redshift , and delivering performant, secure RESTful APIs used across web and mobile platforms. You'll work closely with iOS and Android engineers to ensure seamless end-to-end 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 ❯

and data pipeline design. Hands-on experience with data lakehouse, warehouse, and streaming data architectures. Working knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Databricks, Synapse, Snowflake, Redshift). Experience designing data platforms leveraging PaaS and SaaS solutions. Solid understanding of information governance, metadata management, and master data management principles. Experience leading data design across full project More ❯

and data pipeline design. Hands-on experience with data lakehouse, warehouse, and streaming data architectures. Working knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Databricks, Synapse, Snowflake, Redshift). Experience designing data platforms leveraging PaaS and SaaS solutions. Solid understanding of information governance, metadata management, and master data management principles. Experience leading data design across full project More ❯

and data pipeline design. Hands-on experience with data lakehouse, warehouse, and streaming data architectures. Working knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Databricks, Synapse, Snowflake, Redshift). Experience designing data platforms leveraging PaaS and SaaS solutions. Solid understanding of information governance, metadata management, and master data management principles. Experience leading data design across full project More ❯

and data pipeline design. Hands-on experience with data lakehouse, warehouse, and streaming data architectures. Working knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Databricks, Synapse, Snowflake, Redshift). Experience designing data platforms leveraging PaaS and SaaS solutions. Solid understanding of information governance, metadata management, and master data management principles. Experience leading data design across full project More ❯

and data pipeline design. Hands-on experience with data lakehouse, warehouse, and streaming data architectures. Working knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Databricks, Synapse, Snowflake, Redshift). Experience designing data platforms leveraging PaaS and SaaS solutions. Solid understanding of information governance, metadata management, and master data management principles. Experience leading data design across full project More ❯

ELT processes, automation Technical Requirements: - Strong proficiency in SQL and Python programming - Extensive experience with data modeling and data warehouse concepts - Advanced knowledge of AWS data services, including: S3, Redshift, AWS Glue, AWS Lambda - Experience with Infrastructure as Code using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required Skills 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

persuasively Desirable Skills for the Senior Data Engineer: Experience with event sourcing, dbt, or related data transformation tools Familiarity with PostgreSQL and cloud-native data services (Azure Event Hub, Redshift, Kinesis, S3, Blob Storage, OneLake, or Microsoft Fabric) Understanding of machine learning model enablement and operationalisation within data architectures Experience working within Agile delivery environments If you are an 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 ❯

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 ❯