1 to 25 of 58 Amazon Redshift Jobs in England

Posted Todayjob requisition id: RThe purpose of this role is to oversee the development of our database marketing solutions, using database technologies such as Microsoft SQL Server/Azure, Amazon Redshift, Google BigQuery. The role will be involved in design, specifications, troubleshooting, and issue resolution. The ability to communicate to both technical and non-technical audiences is key. … visit . Role Purpose The purpose of this role is to oversee the development of our database marketing solutions, using database technologies such as Microsoft SQL Server/Azure, Amazon Redshift, Google BigQuery. The role will be involved in design, specifications, troubleshooting, and issue resolution. The ability to communicate to both technical and non-technical audiences is key. More ❯

processing) Apache Spark Streaming, Kafka 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 for this job indicates a More ❯

practices and contribute to team knowledge. Required Skills 3+ years in a data engineering role. Proficient in SQL and Python . Strong experience with AWS services (e.g., Lambda, Glue, Redshift, S3). Solid understanding of data warehousing and modelling: star/snowflake schema Familiarity with Git , CI/CD pipelines, and containerisation (e.g., Docker). Ability to troubleshoot BI More ❯

practices and contribute to team knowledge. Required Skills 3+ years in a data engineering role. Proficient in SQL and Python . Strong experience with AWS services (e.g., Lambda, Glue, Redshift, S3). Solid understanding of data warehousing and modelling: star/snowflake schema Familiarity with Git , CI/CD pipelines, and containerisation (e.g., Docker). Ability to troubleshoot BI More ❯

introduction of streaming and real-time data processing alongside traditional batch systems. Mentoring junior engineers and sharing best practices to strengthen data engineering capability. Tech Stack & Environment AWS ecosystem: Redshift, S3, Glue, Lambda, Step Functions, CloudFormation Core tools: Python, SQL, DBT, Terraform, GitHub, CI/CD Data warehousing: 600TB+ environment with expansion into Databricks BI & analytics: Power BI, Tableau 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 ❯

/CD pipelines, IaC, monitoring systems to ensure scalable, reliable data workflows. You bring professional experience with the following tools : AWS data tooling such as S3/Glue/Redshift/SageMaker. Familiarity with containerization (e.g., Docker/ec2), Orchestration in enterpirse environment (Airflow), Infrastructure automation (Terraform), CI/CD platform (Github Actions & Admin), Password/Secret management (hashicorp More ❯

/CD pipelines, IaC, monitoring systems to ensure scalable, reliable data workflows. You bring professional experience with the following tools : AWS data tooling such as S3/Glue/Redshift/SageMaker. Familiarity with containerization (e.g., Docker/ec2), Orchestration in enterpirse environment (Airflow), Infrastructure automation (Terraform), CI/CD platform (Github Actions & Admin), Password/Secret management (hashicorp More ❯

and big data platforms. • Knowledge of data modeling, replication, and query optimization. • Hands-on experience with SQL and NoSQL databases is desirable. • Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: • Comfortable operating in hybrid environments (cloud and on-prem). • Experience integrating diverse data sources and systems. • Understanding of secure data transfer More ❯

and big data platforms. • Knowledge of data modeling, replication, and query optimization. • Hands-on experience with SQL and NoSQL databases is desirable. • Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: • Comfortable operating in hybrid environments (cloud and on-prem). • Experience integrating diverse data sources and systems. • Understanding of secure data transfer More ❯

Responsibilities Proven experience as a Data Architect or Lead Data Engineer in AWS environments Deep understanding of cloud-native data services: S3, Redshift, Glue, Athena, EMR, Kinesis, Lambda Strong hands-on expertise in data modelling, distributed systems, and pipeline orchestration (Airflow, Step Functions) Background in energy, trading, or financial markets is a strong plus Excellent knowledge of Python, SQL More ❯

Proven experience as a Data Architect or Lead Data Engineer in AWS environments* Deep understanding of cloud-native data services: S3, Redshift, Glue, Athena, EMR, Kinesis, Lambda* Strong hands-on expertise in data modelling, distributed systems, and pipeline orchestration (Airflow, Step Functions)* Background in energy, trading, or financial markets is a strong plus* Excellent knowledge of Python, SQL, and 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 ❯

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 ❯

Requirements Proven experience as a Data Engineer, with a track record of designing and managing scalable data pipelines and infrastructure in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages More ❯

cloud technologies for ETL pipeline, data warehouse and data lake design/building and data movement. AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB . Essential requirements You thrive in problem-solving and analytical thinking You enjoy collaborating with multiple stakeholders in a fast-paced environment Experience in the design More ❯

from a similar environment. The Skill Requirements: Candidates must have a blend of the following: Excellent understanding of AWS Data Platforms, with services such as AWS Glue, S3, Lambda, Redshift, etc. Good understanding of management principles for data pipelines and ETL Good Python and PySpark Use of SQL Data platforms If you have experience migrating from an on-premise More ❯

such as Looker, Tableau, Power Bi or similar Good SQL skills, you know your way around a database. Some exposure to a cloud-based data warehouse such as Snowflake, Redshift, Big Query or similar. Some knowledge of ETL/ELT and data automation. A desire to work with complex Salesforce detail and master that data. Excellent problem-solving skills More ❯

platforms, preferably Azure (AWS, GCP experience is also valuable). Experience managing large and complex datasets, with a strong command of SQL for cloud-based environments (Fabric, Snowflake, BigQuery, Redshift, etc.). A solid understanding of data modelling techniques (star schema, data vault, dimensional modelling). Proficiency in Excel-based data workflows for various Agile Retail projects. Hands-on More ❯

consistency across various data sources. Document test results and provide detailed reports on data quality findings. Required Skills and Experience: Proven experience with AWS services such as EMR, Lambda, Redshift, Firehose, S3, Iceberg, Athena, and DynamoDB. Strong understanding of data ingestion, parsing, aggregation, and schema validation processes. Proficiency in SQL for data querying and validation. Experience with Python for 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 ❯

in SQL and Python Cloud engineering experience with Azure (if you have exp with AWS this would be beneficial) Experience working with cloud-based data platforms such as AWS Redshift or Azure Synapse Understanding of automated Terraform deployment methods A background in leading complex AI/ML/Data initiatives Strong analytical and problem-solving skills with a detail More ❯

What We're Looking For Hands-on Palantir Foundry expertise or transferable, client facing data engineering experience with large-scale data platforms such as: Snowflake, Databricks, AWS Glue/Redshift, Google BigQuery Software engineering skills in Python, Java, or TypeScript/React. Strong data modelling, pipeline development, and API design experience. Excellent problem-solving and communication skills. Why This More ❯

machine learning, and next-gen data architecture. What You’ll Do Build and deliver robust, scalable data pipelines using Python and SQL. Model and transform data in Databricks, AWS Redshift, and other modern platforms. Integrate new systems into our Group Data Warehouse, enabling faster, smarter insights. Collaborate with stakeholders to understand business needs and deliver data solutions that drive 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 ❯