1 to 25 of 154 Remote Amazon Redshift Jobs in England

NumPy, Pandas, SQL Alchemy) and 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-code practices Familiarity with data More ❯

/Data Engineering/BI Engineering experience Understanding of data warehousing, data modelling concepts and structuring new data tables Knowledge of cloud-based MPP data warehousing (e.g. Snowflake, BigQuery, Redshift) Nice to have Experience developing in a BI tool (Looker or similar) Good practical understanding of version control SQL ETL/ELT knowledge, experience with DAGs to manage script More ❯

triage and prioritise platform capabilities to deliver business and customer outcomes. AWS Data Product Development: Lead the development of cloud-native data products using AWS services such as S3, Redshift, Glue, Lambda, and DynamoDB, aligning with business needs. Technical Leadership & Advisory: Act as a trusted AWS expert, advising clients on cloud migration, data strategy, and architecture modernization while working … technical expertise in AWS – Proven experience in designing and implementing cloud-based data architectures, ETL pipelines, and cloud-native applications, using services such as AWS EC2, S3, Lambda, Glue, Redshift, RDS, IAM, and KMS. Leadership & Stakeholder Management – Ability to engage with C-level executives (CDOs, CTOs, CIOs), lead cross-functional teams, and drive technical strategy in complex enterprise environments. More ❯

triage and prioritise platform capabilities to deliver business and customer outcomes. AWS Data Product Development: Lead the development of cloud-native data products using AWS services such as S3, Redshift, Glue, Lambda, and DynamoDB, aligning with business needs. Technical Leadership & Advisory: Act as a trusted AWS expert, advising clients on cloud migration, data strategy, and architecture modernization while working … technical expertise in AWS – Proven experience in designing and implementing cloud-based data architectures, ETL pipelines, and cloud-native applications, using services such as AWS EC2, S3, Lambda, Glue, Redshift, RDS, IAM, and KMS. Leadership & Stakeholder Management – Ability to engage with C-level executives (CDOs, CTOs, CIOs), lead cross-functional teams, and drive technical strategy in complex enterprise environments. More ❯

stack with robust, pragmatic solutions. Responsibilities develop, and maintain ETL/ELT data pipelines using AWS services Data, Databricks and dbt Manage and optimize data storage solutions such as Amazon S3, Redshift, RDS, and DynamoDB. Implement and manage infrastructure-as-code (IaC) using tools like Terraform or AWS CloudFormation. Monitor and optimize the performance, cost, and scalability of More ❯

stack with robust, pragmatic solutions. Responsibilities develop, and maintain ETL/ELT data pipelines using AWS services Data, Databricks and dbt Manage and optimize data storage solutions such as Amazon S3, Redshift, RDS, and DynamoDB. Implement and manage infrastructure-as-code (IaC) using tools like Terraform or AWS CloudFormation. Monitor and optimize the performance, cost, and scalability of More ❯

structured and unstructured data using Python, R, SQL, AWS services and other tools. Build and maintain data repositories using AWS S3 and FSx technologies. Establish data warehousing solutions using Amazon Redshift. Build and maintain standard data models. Develop data quality frameworks, validation processes and KPIs to ensure accuracy and consistency of data pipelines. Implement data versioning and lineage tracking … R&D. Required Knowledge, Skills And Abilities Strong knowledge of data engineering tools such as Python, R and SQL for data processing. Strong proficiency with AWS services particularly S3, Redshift, FSx, Glue, Lambda. Strong proficiency with relational databases. Strong background in data modeling and database design. Familiarity with unstructured database technologies (e.g. NoSQL) and other database types (e.g. Graph More ❯

in a Principal or Lead 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 data architecture, dimensional modelling, and More ❯

in a Principal or Lead 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 data architecture, dimensional modelling, and More ❯

Hands-on experience with AWS Lambda for serverless computing in data workflows. Knowledge of AWS Glue Crawler Kinesis RDS for batch/real-time data streaming Familiarity with AWS Redshift for large-scale data warehousing and analytics. Skillful in implementing data lakes using AWS Lake Formation for efficient storage and retrieval of diverse datasets. Experience with AWS Data Pipeline … solutions. Hands-on experience with AWS DMS (Database Migration Service) for seamless data migration between different databases. Knowledge of AWS Athena for interactive query processing on data stored in Amazon S3. Experience with AWS AppSync for building scalable and secure GraphQL APIs. Qualifications: A minimum of 10 years of experience in data engineering or a related field. Strong background More ❯

. Document data lineage and 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, Kubernetes, Terraform, CI/CD 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 ❯

Warehousing(highly desirable): Experience working 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 files, API’s and event More ❯

thought leader by authoring blogs, 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. You’ll work closely with More ❯

requirements. Design and develop scalable AWS architectures for API-based and data-centric applications. Define data pipelines, ETL processes, and storage solutions using AWS services such as S3, OpenSearch, Redshift, Step Functions, Lambda, Glue, and Athena. Architect RESTful APIs, ensuring security, performance, and scalability. Optimise microservices architecture and API management strategies, leveraging tools such as KONG Gateway, Lambda, and … with a strong focus on AWS cloud services. Expertise in API design, microservices architecture, and cloud-native development. Hands-on experience with AWS services including EKS, Lambda, DynamoDB, S3, Redshift, RDS, Glue, Athena. Strong knowledge of serverless architectures, event-driven patterns, and containerization. Experience designing and implementing secure, scalable, and high-availability architectures. Solid understanding of networking, security, authentication More ❯

cloud platforms (GCP, AWS, Azure) 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 business stakeholders Strategic thinking with More ❯

design decisions. A proven track record in delivering projects and advanced data validation experience is an advantage. Key Skills & Experience Proficiency in one or more database systems such as Amazon Aurora MySQL, Microsoft SQL Oracle, DynamoDB, etc. Expert level hands-on experience in designing, developing, and maintaining complex SQL queries, stored procedures to support various business applications. Perform advanced … scripts and automation tools to streamline data management tasks. Familiarity with version control systems for database schema changes (, Git). Knowledge of AWS DMS, Lambda, S3, Step Functions, CloudWatch, Redshift, Glue, Event Bridge. CI/CD – Pipeline setup and repository (Bitbucket) knowledge. Automated testing design and setup. Experience with large-scale data environments. Data Warehousing concepts, design and loading More ❯

Hive, Spark as well as Apache NiFi. Familiar with containerization and orchestration technologies such as Docker, Kubernetes. Familiar with Time-series or Analytics Databases such as Elasticsearch. Experience with Amazon Web Services using services such as S3, EC2, EMR, Redshift. Familiar with Data Monitoring and Visualisation tools such as Prometheus and Grafana. Familiar with software versioning tools like Git. More ❯

Has extensive experience with at least one major cloud provider (e.g., AWS, Azure, GCP) and their relevant data and ML services. Has experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) and data lake technologies (e.g., S3, ADLS). Has experience with Apache Spark (PySpark). Is familiar with workflow orchestration tools (e.g., Airflow, Prefect, Dagster). Is proficient More ❯

cost-effective, and support both operational and analytical workloads, leveraging cloud technologies (AWS, GCP, Azure). Hybrid Cloud & Data Migration Solutions- Implement cloud-based hybrid data architectures (e.g., Snowflake, Redshift, BigQuery), migrate legacy data systems. Developing innovative solutions: Lead the creation of PoCs and MVPs for Data platforms to host advanced analytics & AI solutions focusing on the needs and More ❯

ideal for someone passionate about using data to support health research and services that positively impact lives. Key Responsibilities: Lead the architecture and delivery of scalable data platforms using Amazon Web Services (AWS) . Build and maintain end-to-end data pipelines and support the team in adopting CI/CD practices. Leverage AWS tools such as S3 , Glue … Redshift , and Lambda to process and analyse data efficiently. Use scripting such as Python , Bash , or R to automate workflows and develop data solutions. Implement version control through Git and GitHub , and contribute to a collaborative development environment. Manage a wide range of databases including MySQL , PostgreSQL , and PostGIS . Provide mentorship and leadership to a small team, encouraging More ❯

dbt) Track record turning research code into production services (CI/CD, containers etc) Strong SQL and data-management skills; experience querying large analytical databases (Snowflake highly desirable, but Redshift/BigQuery/ClickHouse etc. also welcome). PREFERRED QUALIFICATIONS: Meteorological understanding/experience with weather modelling Prior knowledge or experience in the power markets or energy sector. Experience More ❯

SecurityHub, ControlTower, SCPs, TrustedAdvisor, Inspector and Systems Manager. Serverless platforms such as Lambda, SQS, Fargate, and API Gateway. RDS experience and exposure to DataLake/LakeHouse platforms such as RedShift, Glue, and Athena and IAM roles and policies. Deep experience and strong skills with Terraform and Git. Experience troubleshooting server and software configuration issues on both Windows and Linux More ❯

reliable, scalable, and well-tested solutions to automate data ingestion, transformation, and orchestration across systems. Own data operations infrastructure: Manage and optimise key data infrastructure components within AWS, including Amazon Redshift, Apache Airflow for workflow orchestration and other analytical tools. You will be responsible for ensuring the performance, reliability, and scalability of these systems to meet the growing More ❯

It suits someone who thrives in greenfield environments, enjoys client engagement, and values clean, scalable, well-documented engineering. Key Responsibilities: Design and build robust data pipelines using AWS (S3, Redshift, Glue, Lambda, Step Functions, DynamoDB). Deliver ETL/ELT solutions with Matillion and related tooling. Work closely with client teams to define requirements and hand over production-ready … solutions. Own infrastructure and deployment via CI/CD and IaC best practices. Contribute to technical strategy and mentor junior engineers. Requirements: Strong hands-on AWS experience – S3, Redshift, Glue essential. Proven experience building ETL/ELT pipelines in cloud environments. Proficient in working with structured/unstructured data (JSON, XML, CSV, Parquet). Skilled in working with relational More ❯