76 to 100 of 1,433 Amazon Redshift Jobs in the UK

ETL tools (Streamsets, DBT etc.) Hands on experience with Oracle RDBMS Data Migration experience to Snowflake Experience with AWS services such as S3, Lambda, Redshift, and Glue. Strong understanding of data warehousing concepts and data modeling. Excellent problem-solving and communication skills, with a focus on delivering high-quality More ❯

. Translate business requirements into robust, scalable data platform solutions. Design data ingestion, transformation, storage, and access layers using AWS services (e.g., S3, Glue, Redshift, Lambda, Athena). Define data governance, security, and compliance frameworks aligned with public sector standards (e.g., GDPR, GDS, NCSC). Collaborate with stakeholders, engineers More ❯

Stay up to date with the latest trends and best practices in data engineering and cloud technologies, especially AWS services such as S3, Lambda, Redshift, and Glue. Qualifications: Bachelor’s degree in computer science, engineering, or a related field. 5+ years of experience in data engineering, with a strong More ❯

on experience in building data pipelines using tools like Apache Airflow, Spark, or similar. Familiarity with data warehousing concepts and technologies (e.g., Snowflake, BigQuery, Redshift). Excellent problem-solving and communication skills. Nice to Have Experience with CI/CD and containerization (e.g., Docker, Kubernetes). Familiarity with data More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

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. More ❯

that can support the company’s current and future data needs. You will work with modern data warehouse technologies such as Snowflake, BigQuery, or Redshift, selecting the right tools to meet the organisation's needs. You’ll establish standards for data quality and integrity, ensuring the business has access More ❯

while fostering a positive and inclusive team culture What we’re looking for: Hands-on experience building and maintaining cloud-based data systems (e.g., Redshift, BigQuery, Snowflake) Strong coding skills in languages commonly used for data work (e.g., Python, Java, Scala) Deep understanding of ETL/ELT tools and More ❯

Avro , etc. Deep understanding of distributed computing and parallel processing . Experience working on cloud platforms (preferably AWS) and services like S3, EMR, Glue, Redshift, BigQuery . Proficiency in CI/CD pipelines, Docker, Kubernetes, and Terraform . Knowledge of Java, Python, or other JVM-based languages is a More ❯

preferred) Experience with cloud platforms (AWS/Azure) Solid understanding of data architecture, modelling, and ETL/ELT pipelines Experience using tools like Databricks, Redshift, Snowflake, or similar Comfortable working with APIs, CLIs, and orchestration tools like Airflow Confident using Git and familiar with CI/CD processes (Azure More ❯

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. More ❯

or Google). Experience with CI/CD processes and source control tools such as GitHub and GitLab. Experience working with relational databases (Snowflake, Redshift). Strong knowledge of orchestration tools (AirFlow preferred), file storage systems (AWS S3, Google Cloud Storage), partitioning, and real-time data processing. Strong knowledge More ❯

testing across our software, infrastructure, and data pipelines. Key requirements: Technical Skills Proven experience with AWS services (S3, Glue, Lambda, Athena, EMR, Step Functions, Redshift, etc.). Proficient in Terraform, CloudFormation, or AWS SAM for Infrastructure as Code. Skilled in Docker, containerization, and virtualization. Hands-on experience with CI More ❯

design, build, and maintain large scale data solutions and applications using AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB. Your team members will look to you as a trusted expert and will expect you to define the end-to-end More ❯

server) Data Integration Tools: Knowledge of platforms like Airflow, Apache NiFi, or Talend. Data Storage and Modelling: Experience with data warehousing tools (e.g. Snowflake, Redshift, BigQuery) and schema design. Version Control and CI/CD: Familiarity with Git, Docker, and CI/CD pipelines for deployment. Experience 2+ years More ❯

and their data-specific services Proficiency in Python, SQL, and data orchestration tools (e.g., Airflow, DBT) Experience with modern data warehouse technologies (BigQuery, Snowflake, Redshift, etc.) Strong understanding of data modeling, data governance, and data quality principles Excellent communication skills with the ability to translate complex technical concepts for More ❯

and their data-specific services Proficiency in Python, SQL, and data orchestration tools (e.g., Airflow, DBT) Experience with modern data warehouse technologies (BigQuery, Snowflake, Redshift, etc.) Strong understanding of data modeling, data governance, and data quality principles Excellent communication skills with the ability to translate complex technical concepts for More ❯

real-time data pipelines using AWS services such as AWS EMR, AWS Glue, Glue Catalog, and Kinesis. Additionally, they create data layers on AWS RedShift, Aurora, and DynamoDB. The data engineer also migrates data using AWS DMS and is proficient with various AWS Data Platform components, including S3, RedShift, RedShift Spectrum, AWS Glue with Spark, AWS Glue with Python, Lambda functions with Python, AWS Glue Catalog, and AWS Glue Databrew. They are experienced in developing batch and real-time data pipelines for Data Warehouse and Datalake, utilizing AWS Kinesis and Managed Streaming for Apache Kafka. They are More ❯

and optimise Kafka clusters for real-time data streaming. Oversee and maintain containerized workloads using EKS (Kubernetes on AWS) . Support data infrastructure, including Amazon Redshift for analytics and storage. Implement security best practices and compliance controls within cloud environments. Collaborate with development, security, and operations teams to … such as Sentry and Grafana). Design procedures for system troubleshooting and maintenance. Required Skills & Experience Strong experience with AWS services , particularly EKS, Kafka, Redshift, and CloudWatch . Hands-on experience with Kubernetes and container orchestration. Experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, or similar More ❯

Strong stakeholder experience with an ability to work with both technical and non-technical stakeholders.//Proven experience with AWS services (e.g. S3, Redshift, Lambda, ECS, Eventbridge, CloudWatch, Athena etc.).//Proficient in Python & SQL.//Experience with Terraform to manage IaC.//Strong More ❯