26 to 50 of 58 Amazon Redshift Jobs in England

Collaborative, curious, and happy to work in a self-organising, fast-paced environment. Nice-to-Have Skills : ·Experience with GCP/BigQuery or other cloud data warehouses (e.g., Snowflake, Redshift). ·Familiarity with data orchestration tools (e.g., Airflow). ·Experience with data visualisation platforms (such as Preset.io/Apache Superset or other). ·Exposure to CI/CD pipelines More ❯

and eventual consistency systems using Kafka, .Net, Java, REST APIs, AWS, Terraform and DevOps Nice to have:experience in data pipping and modelling using SQL, DBT, ETL, Data Warehousing, Redshift and Python, and ecommerce and mobile applications background Additional Information Were a community here that cares as much about your life outside work as how you feel when youre More ❯

Knowledge and interest in financial services and products Proven background of working in an analytical role Experience working with cloud data platforms such as Snowflake, Google (Big Query), AWS (Redshift), Azure or others Fluent in SQL Expert in data manipulation and analysis to provide actionable insights through data storytelling Experience using data analysis languages like Python or R Excellent More ❯

consultants. Knowledge and Skills: Knowledge - Broad data management technical knowledge so as to be able to work across full data cycle. - Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD - Coding experience in Apache Spark, Iceberg or Python (Pandas) - Experience in change and release management. - Experience in Database Warehouse … procedures. Technical Essentials: - Expertise across data warehouse and ETL/ELT development in AWS preferred with experience in the following: - Strong experience in some of the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB - Good experience with DBT, Apache Iceberg, Docker, Microsoft BI More ❯

Hands-on with Docker and Kubernetes for containerization and orchestration. Strong experience with REST APIs, FastAPI/Flask, and backend microservices . Solid database skills ( PostgreSQL, MySQL, DynamoDB, MongoDB, Redshift, Snowflake ). Excellent knowledge of CI/CD pipelines and DevOps practices. Experience with Agile/Scrum delivery models . Strong communication and ability to mentor junior developers More ❯

data manipulation techniques. Excellent analytical, problem-solving, and critical thinking skills. Proven ability to communicate technical findings to non-technical stakeholders. Preferred: Experience with cloud data platforms (e.g., AWS Redshift, Google BigQuery, Snowflake). Familiarity with A/B testing, forecasting, and predictive modelling techniques. Experience in eCommerce as well as Finance and Healthcare industries. This fantastic new role More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

years across Data/Software Engineering, Data Analysis. SQL & Python: schema design, transformations, query optimisation, automation, testing. Track record of buildingETL/ELT pipelines into modern warehouses (BigQuery, Snowflake, Redshift). Familiar with tools like Dagster, Airflow, Prefect, dbt, Dataform, SQLMesh. Cloud experience (we're on GCP) + containerisation (Docker, Kubernetes). Strong sense of ownership over data standards More ❯

Skillset Delivery experience Building solutions in snowflake implementing data warehousing solutions using Snowflake and AWS Hands-on experience with AWS services such as Glue (Spark), Lambda, Step Functions, ECS, Redshift, and SageMaker. Enthusiasm for cross-functional work and adaptability beyond traditional data engineering. Examples like building APIs, integrating with microservices, or contributing to backend systems - not just data pipelines … strong hands-on programming skills and software engineering fundamentals, with experience building scalable solutions in cloud environments (AWS preferred) Extensive experience in AWS services, e.g. EC2, S3, RDS, DynamoDB, Redshift, Lambda, API Gateway Solid foundation in software engineering principles, including version control (Git), testing, CI/CD, modular design, and clean code practices. Experience developing reusable components and APIs … preferred for data processing, automation, and pipeline development AWS or Snowflake certifications are a plus Hands-on experience with AWS services such as Glue (Spark), Lambda, Step Functions, ECS, Redshift, and SageMaker. Enthusiasm for cross-functional work and adaptability beyond traditional data engineering. Examples like building APIs, integrating with microservices, or contributing to backend systems - not just data pipelines More ❯

and creating/executing tests Requirements Strong experience as a Data Engineer (migrating Legacy systems onto AWS, building data pipelines) Strong Python experience Tech stack experience required: AWS Glue, Redshift, Lambda, PySpark, Airflow SSIS or SAS experience (Desirable) Benefits Salary up to £57,500 + up to 20% bonus Hybrid working: 1 to 2 days a week in the More ❯

and creating/executing tests Requirements Strong experience as a Data Engineer (migrating legacy systems onto AWS, building data pipelines) Strong Python experience Tech stack experience required: AWS Glue, Redshift, Lambda, PySpark, Airflow SSIS or SAS experience (Desirable) Benefits Salary up to £57,500 + up to 20% bonus Hybrid working: 1 to 2 days a week in the More ❯

on data architecture Strong proficiency in Python and SQL, with the ability to manipulate and analyse large datasets Hands-on experience with Kafka for stream processing and AWS (particularly Redshift and S3) Skilled in implementing testing and validation strategies to ensure data quality Familiar with version control systems such as Git and working in Agile, collaborative environments Self-driven More ❯

office) Role Responsibilities: Develop and deliver the group-wide data and analytics roadmap. Lead on data engineering and reporting, with hands-on expertise across Azure SQL, Power BI, AWS Redshift and similar platforms. Consolidate disparate systems (ERP, EPOS, WMS, ecommerce) into a reliable, scalable reporting framework. Architect and implement integrations, middleware, and data warehousing solutions. Produce, manage, and optimise More ❯

or equivalent) Ability to leverage data to generate customer insights and actionable recommendations Proficiency in SQL Familiarity working in the big data warehouse environment for data analysis (e.g., AWS Redshift, Snowflake, Microsoft Azure) Ability to create charts and dashboards using data visualisation tools (e.g., Tableau, Power BI etc.) Desirable criteria: Experience with another programming language, such as Python or More ❯

will play a pivotal role in designing and implementing data warehousing solutions using Snowflake and AWS. You will help drive the evolution of data architecture as we move from Redshift to Snowflake. Hands-on experience with AWS services such as Glue (Spark), Lambda, Step Functions, ECS, Redshift, and SageMaker. Conducting code reviews, mentoring through pair programming. Building APIs … like GitHub Actions, Jenkins, AWS CDK, CloudFormation, Terraform. Key Responsibilities: Design and implement scalable, secure, and cost-efficient data solutions on AWS, leveraging services such as Glue, Lambda, S3, Redshift, and Step Functions. Lead the development of robust data pipelines and analytics platforms, ensuring high availability, performance, and maintainability. Demonstrate proficiency in software engineering principles, contributing to the development More ❯

FlowFiles,Processors,ControllerServices, Schedulers,WebUI. Experiencedesigningandoptimizingdataflowsforbatch,real-timestreaming,and event-drivenarchitectures. Abilitytoidentifyandresolveflowissues,optimizeperformance,andimplementerror handlingstrategies. OptionalscriptingskillsforcreatingcustomNiFiprocessors. Programming&DataTechnologies: ProficiencyinJavaandSQL. ExperiencewithC#andScalaisaplus. ExperiencewithETLtoolsandbigdataplatforms. Knowledgeofdatamodeling,replication,andqueryoptimization. Hands-onexperiencewithSQLandNoSQLdatabasesisdesirable. Familiaritywithdatawarehousingsolutions(e.g.,Snowflake,Redshift,BigQuery)would bebeneficial. DataPlatformManagement: Comfortableoperatinginhybridenvironments(cloudandon-prem). Experienceintegratingdiversedatasourcesandsystems. Understandingofsecuredatatransferprotocolsanddisasterrecoveryplanning. CI/CD&DevOpsPractices: ExperienceworkingwithCI/CDpipelinestoautomatedeploymentofNiFiflowsanddata infrastructurecomponents. FamiliaritywithtoolssuchasGit,Jenkins,AzureDevOps,orsimilar. WaysofWorking: ComfortableworkinginAgile/Scrumenvironments,participatinginsprintplanning, stand-ups More ❯

FlowFiles,Processors,ControllerServices, Schedulers,WebUI. Experiencedesigningandoptimizingdataflowsforbatch,real-timestreaming,and event-drivenarchitectures. Abilitytoidentifyandresolveflowissues,optimizeperformance,andimplementerror handlingstrategies. OptionalscriptingskillsforcreatingcustomNiFiprocessors. Programming&DataTechnologies: ProficiencyinJavaandSQL. ExperiencewithC#andScalaisaplus. ExperiencewithETLtoolsandbigdataplatforms. Knowledgeofdatamodeling,replication,andqueryoptimization. Hands-onexperiencewithSQLandNoSQLdatabasesisdesirable. Familiaritywithdatawarehousingsolutions(e.g.,Snowflake,Redshift,BigQuery)would bebeneficial. DataPlatformManagement: Comfortableoperatinginhybridenvironments(cloudandon-prem). Experienceintegratingdiversedatasourcesandsystems. Understandingofsecuredatatransferprotocolsanddisasterrecoveryplanning. CI/CD&DevOpsPractices: ExperienceworkingwithCI/CDpipelinestoautomatedeploymentofNiFiflowsanddata infrastructurecomponents. FamiliaritywithtoolssuchasGit,Jenkins,AzureDevOps,orsimilar. WaysofWorking: ComfortableworkinginAgile/Scrumenvironments,participatinginsprintplanning, stand-ups More ❯

Business Intelligence Analyst/BI Analyst you'll be the first hire within this area, supported by the Head of Finance you'll oversee the implementation of the AWS Redshift Data Warehouse that has been built by a tech consultancy and take ownership of implementing PowerBI into the business to enable data informed decisions that drive efficiency and revenue. More ❯

to reduce time-to-production for experiments and prototypes. Design and optimize data wrangling and transformation workflows using Python. Leverage AWS cloud services (EC2, S3, Lambda, SageMaker, RDS, DynamoDB, Redshift, etc.) to build robust, scalable, and cost-effective solutions. Apply AIOps practices to enhance monitoring, automation, and resilience of ML systems. Implement best practices in data engineering, version control … background in data structures, algorithms, and software engineering principles. Advanced proficiency in Python for data wrangling, pipeline automation, and ML workflows. Expertise in AWS services, including databases (RDS, DynamoDB, Redshift) and machine learning/AI (SageMaker, AI/ML frameworks). Hands-on experience with ML pipeline orchestration, CI/CD, and deployment automation. Deep understanding of ML Ops More ❯

to London. This role is ideal for someone with strong experience in data migration, ETL (both batch and real-time), and data warehouse development. What you'll need: DataStage Redshift QuickSight S3 Java SQL Relational databases GitHub/lab experience Experience with DevSecOps and building scalable data platforms Nice to have: Data quality expertise XML knowledge AWS Data Speciality More ❯

with a focus on data projects You have experience of establishing data analytics and supporting AI solutions You have a good working experience of AWS (e.g. S3, Kinesis, Glue, Redshift, Lambda and EMR) and/or Azure data services (e.g. ADF, Synapse, Fabric, Azure Functions) You have advanced client and stakeholder management skills What's in it for you More ❯

with a focus on data projects You have experience of establishing data analytics and supporting AI solutions You have a good working experience of AWS (e.g. S3, Kinesis, Glue, Redshift, Lambda and EMR) and/or Azure data services (e.g. ADF, Synapse, Fabric, Azure Functions) You have advanced client and stakeholder management skills What's in it for you 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 ❯

scientists, and engineers to unlock automation, enable BI, and increase advanced analytics. What You'll Be Doing: Designing and building robust data pipelines using AWS Glue, Lambda, S3, and Redshift Leading the migration of legacy systems to a modern AWS architecture Ensuring data quality, integrity, and performance across platforms Developing scalable lakehouse and warehouse solutions Operationalizing machine learning models … Mentoring junior engineers and sharing best practices Staying ahead of the curve with emerging data technologies What You'll Bring: Solid hands-on experience with AWS (Glue, Lambda, S3, Redshift, EMR) Strong Python, SQL, and PySpark skills Deep understanding of data warehousing and lakehouse concepts Problem-solving mindset with a focus on performance and scalability Excellent communication skills across More ❯

journey to Snowflake-based data warehousing solutions within an AWS environment. Design and implement scalable, secure, and cost-efficient data solutions using AWS services such as Glue, Lambda, S3, Redshift, and Step Functions. Develop robust data pipelines and analytics platforms, ensuring high availability, performance, and maintainability. Drive automation and CI/CD practices for data workflows, ensuring reliable deployment … experience as a data engineer with a strong focus on Snowflake and AWS services in large-scale enterprise environments Extensive experience with AWS services (e.g., EC2, S3, RDS, DynamoDB, Redshift, Lambda, API Gateway) Strong SQL skills for complex data queries and transformations Python programming for data processing and analysis is a plus Strong leadership, communication, and collaboration skills For More ❯