1 to 25 of 60 Amazon Redshift Jobs in England

strategic business decisions. Responsibilities for the AWS Data Engineer: Design, build and maintain scalable data pipelines and architectures within the AWS ecosystem Leverage services such as AWS Glue, Lambda, Redshift, EMR and S3 to support data ingestion, transformation and storage Work closely with data analysts, architects and business stakeholders to translate requirements into robust technical solutions Implement and optimise More ❯

anomaly detection, and GenAI-powered automation Support GenAI initiatives through data readiness, synthetic data generation, and prompt engineering. Mandatory Skills: Cloud Platforms:Deep experience with AWS (S3, Lambda, Glue, Redshift) and/or Azure (Data Lake, Synapse). Programming & Scripting:Proficiency in Python, SQL, PySpark etc. ETL/ELT & Streaming:Expertise in technologies like Apache Airflow, Glue, Kafka, Informatica More ❯

Data Engineers to join a large on prem to AWS migration programme in replicating data pipelines in readiness for a lift and shift to the cloud. Essential: AWS and Redshift In full: Role purpose Reporting to the Lead Data Engineer, the Data Engineer is responsible for designing and maintaining scalable data pipelines, ensuring data availability, quality, and performance to More ❯

based architecture. You will need to have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (e.g., S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise in ETL/ELT More ❯

based architecture. You will need to have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (e.g., S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise in ETL/ELT More ❯

with analysts and architects to ensure compliance with government security standards. Troubleshoot and resolve issues in complex cloud environments. Essential Skills Strong experience with AWS services (Glue, Lambda, S3, Redshift, IAM). Proficiency in Python and SQL for data engineering tasks. Knowledge of data modelling, ETL frameworks, and best practices. Familiarity with security and compliance in government or regulated More ❯

with analysts and architects to ensure compliance with government security standards. Troubleshoot and resolve issues in complex cloud environments. Essential Skills Strong experience with AWS services (Glue, Lambda, S3, Redshift, IAM). Proficiency in Python and SQL for data engineering tasks. Knowledge of data modelling, ETL frameworks, and best practices. Familiarity with security and compliance in government or regulated More ❯

or dbt. Strong SQL skills and experience with cloud platforms (Azure preferred). Solid programming background in Python, Scala, or Java. Knowledge of data warehousing solutions (e.g. Snowflake, BigQuery, Redshift). Strong understanding of data governance, security, and compliance (experience within financial services is a plus). Leadership experience, with the ability to mentor, influence, and set technical direction. More ❯

persuasively Desirable Skills for the Senior Data Engineer: Experience with event sourcing, dbt, or related data transformation tools Familiarity with PostgreSQL and cloud-native data services (Azure Event Hub, Redshift, Kinesis, S3, Blob Storage, OneLake, or Microsoft Fabric) Understanding of machine learning model enablement and operationalisation within data architectures Experience working within Agile delivery environments If you are an More ❯

s Data Governance and Data Classification policies. Maintain data dictionary. Maintain business level data model. Recommending and introducing new technology where needed. Core: Cloud data platforms (e.g. Snowflake, BigQuery, Redshift) Data transformation technology such as DBT Visual Studio Code Python CI automation systems such as Jenkins A git-based source control system such as BitBucket Data Warehouse/Kimball More ❯

with 2+ years in a technical leadership or management role Strong technical proficiency in data modelling, data warehousing, and distributed systems Hands-on experience with cloud data services (AWS Redshift, Glue, EMR or equivalent) Solid programming skills in Python and SQL Familiarity with DevOps practices (CI/CD, Infrastructure as Code - e.g., Terraform) Excellent communication skills with both technical More ❯

. Hands-on experience with data orchestration tools (Airflow, dbt, Dagster, or Prefect). Solid understanding of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift). Experience with streaming technologies (Kafka, Kinesis, or similar). Strong knowledge of data modelling, governance, and architecture best practices . Excellent leadership, communication, and stakeholder management skills. NICE More ❯

office. A team-led hybrid working arrangement is in place. About you To be successful in this role it's essential you have: Extensive experience with AWS (S3, Glue, Redshift, SageMaker) Experience of building and automating data pipelines in finance The ability to demonstrate, automate and manage data systems so they run smoothly and can grow easily. Familiarity with More ❯

the organisation. What you'll be doing: Design, develop, and maintain scalable data architectures and ETL pipelines Build and manage data models and data warehouse solutions (Airflow, dbt, and Redshift) Write clean, efficient Python and SQL code for data processing and transformation Integrate data from internal and third-party APIs and services Optimise data pipelines for performance, scalability, and More ❯

teams as needed. Skills required to contribute: Years of overall Data and Analytics experience with 2. Minimum 10+ years in AWS data platform including AWS S3, AWS Glue, AWS Redshift, AWS Athena, AWS Sagemaker, AWS Quicksight and AWS MLOPS 3. Snowflake DWH architecture, Snowflake Data Sharing, Snowpipe, Polaris catalog and data governance (meta data/business catalogs). 4. More ❯

everyone feels supported to learn and grow. Skills & Experience We re Looking For Technical Expertise Hands-on experience with modern data stacks (e.g. Dataform, dbt, Snowflake/BigQuery/Redshift). Expert SQL skills, including advanced analytics and performance optimisation. Strong experience with BI tools (Looker, Power BI, Tableau) and data storytelling. Skilled in data modelling, ELT/ETL More ❯

may be a great fit if you have experience with any of the following... Workflow orchestration tooling (e.g. Prefect, Airflow, Dagster) Experience with cloud data warehouses (e.g. BigQuery, Snowflake, Redshift) Data transformation tools (e.g. dbt) and data quality frameworks (e.g. Great Expectations) Backend Python frameworks (e.g. Django, FastAPI, Flask) for API development Modern data processing libraries (e.g. Polars, DuckDB More ❯

leveraging data to improve the OTM users and agents experience. This role would be suited to an individual with a background in Python, SQL, AWS, Looker, PyTorch, Airflow and Redshift/Postgres. The candidate must be able to exhibit proficiency in working with large volumes of data, automating data loads, and the ability to understand end user requirements with … goal of building a solution to provide high quality data processing and analysis as well as building APIs. RESPONSIBILITIES D evelop data pipelines using Python and Airflow Data warehousing (Redshift/Spectrum) Develop data solutions to address business needs Maintain existing reports and improve their performance QUALIFICATIONS Bachelors degree in Computer Science, Data Science, Mathematics, Engineering or equivalent experience … query performance. Strong skills in Python Experience with AWS or GCP Demonstrated experience and responsibility with data, processes, and building ETL pipelines. Experience with cloud data warehouses such as Amazon Redshift, and Google BigQuery. Building visualizations using tools such as Looker studio or equivalent Experience in designing ETL/ELT solutions, preferably using tools like Airflow or AWS More ❯

experience in similar environments is essential. The Skill Requirements: We're looking for candidates with a blend of the following: Strong knowledge of AWS data services (Glue, S3, Lambda, Redshift, etc.) Solid understanding of ETL processes and data pipeline management Proficiency in Python and PySpark Experience working with SQL-based platforms Previous involvement in migrating on-premise solutions to More ❯

SC cleared, or eligible to obtain SC-level security clearance Job description We are looking for a developer with expertise in Python, AWS Glue, step function, EMR cluster and redshift, to join our AWS Development Team. You will be serving as the functional and domain expert in the project team to ensure client expectations are met. The role involves More ❯

what to do, run some whiteboard design sessions (realising you've used a permanent marker, you quickly leave the room) Qualifications Data Warehousing, Data Modelling, Database Design, ETL AWS Redshift, AWS Glue, S3, SQL Server, Power BI Cloud/DevOps AWS, Docker, Terraform Bitbucket, Bamboo, CI/CD deploy pipeline Agile, pair programming, code reviews Additional Information Were a More ❯

Version Control: Git WHAT YOU NEED Essential: 4+ years in Data/Analytics Engineering or BIStrong SQL skills (production-level)DBT experience (essential)Cloud data warehouse experience (BigQuery, Snowflake, Redshift)Data modeling expertiseUser acquisition or marketing analytics backgroundMobile app or gaming industry experience (highly preferred)Strong communication skillsSelf-starter who works autonomouslyDegree in Engineering, Computer Science, Maths, or related More ❯

Data Engineer in a cloud environment, with openness to various data platforms including AWS, Azure, and Google Cloud. Strong knowledge of data services across multiple platforms (e.g., AWS S3, Redshift, Glue, Azure Blob Storage, Google BigQuery). Expertise in data modelling (Dimensional, Data Vault, Enterprise). Experience designing and implementing modern data architectures. Proficiency with integration/orchestration tools More ❯

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 ❯

models, tests, documentation, version control. Understanding of data warehousing concepts (star schemas, snowflake, slowly changing dimensions, partitioning, clustering). Experience working in a modern data stack (e.g. BigQuery, Snowflake, Redshift, Databricks, etc.) Comfortable working downstream (with BI/analytics users) and upstream (pipelines, ingestion) contexts. Familiarity with BI tools (we use Thoughtspot and Power BI). Proficient in Python. More ❯