26 to 50 of 866 Amazon Redshift Jobs in the UK

and maintain robust data pipelines using AWS services (Glue, Lambda, Step Functions, S3, etc.) Develop and optimize data lake and data warehouse solutions using Redshift, Athena, and related technologies Collaborate with data scientists, analysts, and business stakeholders to understand data requirements Ensure data quality, governance, and compliance with financial More ❯

development and implementation of complex data pipelines and ETL/ELT processes using cloud-native technologies (e.g. AWS Glue AWS Lambda AWS S3 AWS Redshift AWS EMR). Develop and maintain data quality checks data validation rules and data lineage documentation. Collaborate with data analysts data scientists business stakeholders More ❯

in a startup or fast-moving environment. Technical Stack : Languages/Tools: Python (REST API integrations), DBT, Airbyte, GitHub Actions Modern Data Warehousing: Snowflake, Redshift, Databricks, or BigQuery. Cloud & Infra: AWS (ECS, S3, Step Functions), Docker (Kubernetes or Fargate a bonus) Data Modelling : Strong grasp of transforming structured/ More ❯

in a startup or fast-moving environment. Technical Stack : Languages/Tools: Python (REST API integrations), DBT, Airbyte, GitHub Actions Modern Data Warehousing: Snowflake, Redshift, Databricks, or BigQuery. Cloud & Infra: AWS (ECS, S3, Step Functions), Docker (Kubernetes or Fargate a bonus) Data Modelling : Strong grasp of transforming structured/ More ❯

design sessions. Key Requirements Why Holland & Barrett? Must-Have: Strong experience with AWS services: Glue, Lambda, S3, Athena, Step Functions, EventBridge, EMR, EKS, RDS, Redshift, DynamoDB. Strong Python development skills. Proficient with Docker, containerization, and virtualization. Hands-on experience with CI/CD, especially GitLab CI. Solid experience with More ❯

or similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or GCP (e.g. S3, EMR, Redshift, Glue, Azure Data Factory, Databricks, BigQuery, Dataflow, Dataproc) Would you like to join us as we work hard, have fun and make history? Apply More ❯

from various sources into AWS data stores for both batch and streaming data ingestion. AWS Expertise: Utilize your expertise in AWS services such as Amazon EMR, S3, AWS Glue, Amazon Redshift, AWS Lambda, and more to build and optimize data solutions. Data Modeling: Design and implement data … a related field. 5 to 8 years of experience in data engineering, including working with AWS services. Proficiency in AWS services like S3, Glue, Redshift, Lambda, and EMR. Knowledge of Cloudera-based Hadoop is a plus. Strong ETL development skills and experience with data integration tools. Knowledge of data More ❯

ingest, process, and store large sets of financial data from various internal and external sources. Cloud Infrastructure Management : Leverage AWS services such as S3, Redshift, Lambda, Glue, and others to develop and maintain robust cloud-based data infrastructure. Automation : Use Terraform to automate infrastructure provisioning, deployment, and configuration, ensuring … efficiency and repeatability in cloud environments. Database Design & Optimisation : Design and optimise complex SQL queries, and relational databases (e.g., Amazon Redshift, PostgreSQL, MySQL) to enable fast, efficient data retrieval and analytics. Data Transformation : Apply ETL/ELT processes to transform raw financial data into usable insights for business … industries. Strong understanding of data engineering concepts, including data modelling, ETL/ELT processes, and data warehousing. Proven experience with AWS services (e.g., S3, Redshift, Lambda, ECS, ECR, SNS, Eventbridge, CloudWatch, Athena etc.) for building and maintaining scalable data solutions in the cloud. Technical Skills (must have): Python: Proficient More ❯

role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of More ❯

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 More ❯

or similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or GCP (e.g. S3, EMR, Redshift, Glue, Azure Data Factory, Databricks, BigQuery, Dataflow, Dataproc Would you like to join us as we work hard, have fun and make history? Apply More ❯

platforms (AWS, GCP, Azure) and related tools (e.g., Kubernetes, Terraform, CloudFormation). Experience with modern data platforms, including data lakes, data warehouses (e.g., Snowflake, Redshift, BigQuery), and real-time data processing. Proficiency in data modelling, ETL/ELT pipelines, and data integration tools. Strong understanding of security, compliance, and More ❯

role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of More ❯

role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of More ❯

role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of More ❯

and Portfolio managers will be required. Responsibilities: Building Data pipelines in AWS platform utilizing existing tools like Cron, Glue, Eventbridge, Python based ETL, AWS Redshift Working closely with data vendors such as Bloomberg, Refinitiv, Exchanges etc. Normalizing/standardizing vendor data , firm data for firm consumption Help Support and More ❯

role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of More ❯

conceptual, logical and physical data modelling techniques as well as dimensional modelling techniques. Experience using cloud data warehouse technology- Snowflake (preferred), Google BigQuery, AWS Redshift or Azure Synapse and experience working with key services on either GCP, AWS or Azure. Key services include cloud storage, containerisation, event-driven services More ❯

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 More ❯

platforms (AWS, GCP, Azure) and related tools (e.g., Kubernetes, Terraform, CloudFormation). Experience with modern data platforms, including data lakes, data warehouses (e.g., Snowflake, Redshift, BigQuery ), and real-time data processing. Proficiency in data modelling, ETL/ELT pipelines, and data integration tools. Strong understanding of security, compliance, and More ❯

your technical skills Demonstrable experience of utilising strong communication and stakeholder management skills when engaging with customers Significant experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) Strong proficiency in SQL and experience with relational databases such as MySQL, PostgreSQL, or … Oracle Experience with big data technologies such as Hadoop, Spark, or Hive Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow Proficiency in Python and at least one other programming language such as Java, or Scala Willingness to mentor more junior More ❯

design and modelling, including conceptual, logical, physical, and dimensional modelling techniques. Knowledge of cloud data warehouse technologies such as Snowflake (preferred), Google BigQuery, AWS Redshift, or Azure Synapse, and familiarity with GCP, AWS, or Azure services like cloud storage, containerisation, orchestration, and security. Experience working in Agile environments, using More ❯

grade data solutions, fostering a culture of innovation, collaboration, and continuous learning. Key Responsibilities: Design, develop, test, and deploy data integration pipelines in AWS (Redshift, Glue, Athena, Lambda, S3). Lead and mentor a team of Data Engineers, guiding their technical work and professional growth. Create technical documentation such More ❯

experience in data engineering, data architecture, or software engineering. Proficiency in Python and SQL Proficient in AWS data services such as S3, Glue, Athena, Redshift, EMR, Kinesis, Lambda, etc. Strong knowledge of data lake concepts, architectures, and design patterns. Experience in building and managing data pipelines using tools such More ❯

platforms (AWS, GCP, Azure) and related tools (e.g., Kubernetes, Terraform, CloudFormation). Experience with modern data platforms, including data lakes, data warehouses (e.g., Snowflake, Redshift, BigQuery), and real-time data processing. Proficiency in data modeling, ETL/ELT pipelines, and data integration tools. Strong understanding of security, compliance, and More ❯