1 to 25 of 201 Remote Amazon Redshift Jobs in the UK

teams to understand business objectives, identify data requirements, and define analytics goals. Develop and implement data analysis strategies using AWS analytics services, such as Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight. Design and build robust data pipelines and ETL processes to extract, transform … techniques to perform predictive and prescriptive analyses, clustering, segmentation, and pattern recognition. Identify key metrics, develop meaningful KPIs, and build dashboards and visualisations using Amazon QuickSight to enable data-driven decision-making. Conduct exploratory data analysis to uncover trends, patterns, and insights that inform product enhancements, user behaviour, and … 2.Proven experience as a Data Scientist, preferably in a cloud-based environment using AWS analytics services. 3.Strong proficiency in AWS analytics services, such as Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight. 4.Solid understanding of data modelling, ETL processes, and data warehousing concepts. 5.Proficiency More ❯

that address complex business requirements and drive decision-making. Your skills and experience Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR , Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS and AWS Step Functions. Programming Skills: Strong experience … and Scala. Expertise in Data Storage Technologies: In-depth knowledge of Data Warehouse, Database technologies, and Big Data Eco-system technologies such as AWS Redshift, AWS RDS, and Hadoop. Experience with AWS Data Lakes: Proven experience working with AWS data lakes on AWS S3 to store and process both More ❯

SQLAlchemy, GitLab, Athena. Your Trusted Companions : Docker, Snowflake, MongoDB, Relational Databases (eg MySQL, PostgreSQL), Dagster, Airflow/Luigi, Spark, Kubernetes. Your AWS Kingdom : Lambda, Redshift, EC2, ELB, IAM, RDS, Route53, S3-the building blocks of cloud mastery. Your Philosophy : Continuous integration/deployments, (CI/CD) automation, rigorous code More ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

recommend improvements for data ownership and stewardship. Qualifications Programming: Python, SQL, Scala, Java. Big Data: Apache Spark, Hadoop, Databricks, Snowflake, etc. Cloud: AWS (Glue, Redshift), Azure (Synapse, Data Factory, Fabric), GCP (BigQuery, Dataflow). Data Modelling & Storage: Relational (PostgreSQL, SQL Server), NoSQL (MongoDB, Cassandra), Dimensional modelling. DevOps & Automation: Docker More ❯

dbt or Google Cloud Platform or related technologies. • Experience with other cloud platforms (e.g. AWS, Azure, Snowflake) and data warehouse/lakehouse technologies (e.g. Redshift, Databricks, Synapse) • Knowledge of distributed big data technologies. • Proficiency in Python. • Familiarity with data governance and compliance frameworks. Your characteristics as a Consultant will More ❯

presenting at webinars, and engaging in external speaking opportunities. Technical Delivery Excellence You’ll design and optimise cloud-based data architectures (e.g. Snowflake, Databricks, Redshift, Google BigQuery, Azure Synapse) to support advanced analytics. You’ll build and automate scalable, secure, and high-performance data pipelines handling diverse data sources. 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 ❯

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 ❯

the client's enterprise strategy. Proven experience as a Data Solution Architect, with expertise in various AWS services such as EC2, S3, Aurora, DynamoDB, Redshift, Lambda, Glue, Athena, Quicksight, and Sagemaker, among others. Proficiency in Snowflake's architecture and familiarity with its features, including Snowpipe, Streams, and Tasks for More ❯

on a data warehouse solution irrespective of underlying technology. Experience using cloud data warehouse technology would also be beneficial - Snowflake (preferred), Google BigQuery, AWS Redshift or Azure Synapse. Data Pipeline(highly desirable): Demonstrable experience working with data from a wide variety of data sources including different database platforms, flat More ❯

presenting at webinars, and engaging in external speaking opportunities. Technical Delivery Excellence You'll design and optimise cloud-based data architectures (e.g. Snowflake, Databricks, Redshift, Google BigQuery, Azure Synapse) to support advanced analytics. You'll build and automate scalable, secure, and high-performance data pipelines handling diverse data sources. More ❯

expert-level SQL across multiple database platforms Hands-on experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake, BigQuery, Redshift) Strong understanding of data modelling, schema design, and building maintainable ELT/ETL pipelines Experience with cloud platforms (AWS, Azure, GCP) and infrastructure-as More ❯

a focus on building and maintaining data pipelines. Commercial awareness of the e-commerce industry Proficiency in working with AWS data services (e.g. S3, Redshift, Glue, Lambda). Strong understanding of Power BI for dashboard creation and data visualization. Experience with Google Analytics 4 for data integration and reporting. More ❯

and unstructured data from diverse sources. Strong knowledge of SQL/NoSQL databases and cloud data warehouse technology such as Snowflake/Databricks/Redshift/BigQuery, including performance tuning and optimisation. Understanding of best practices for designing scalable and efficient data models, leveraging dbt for transformations. Familiarity with More ❯

and unstructured data from diverse sources. Strong knowledge of SQL/NoSQL databases and cloud data warehouse technology such as Snowflake/Databricks/Redshift/BigQuery, including performance tuning and optimisation. Understanding of best practices for designing scalable and efficient data models, leveraging dbt for transformations. Familiarity with More ❯