1 to 25 of 52 Permanent Amazon Redshift Jobs in the South East

Python and PySpark for data processing and automation. Strong command of SQL for data querying, transformation, and performance tuning. Deep experience with cloud platforms , preferably AWS (e.g., S3, Glue, Redshift, Athena, EMR, Lambda). Experience with Azure or GCP is a plus. Experience building and managing data lakes and data warehouses. Strong understanding of distributed systems and big data More ❯

Python and PySpark for data processing and automation. Strong command of SQL for data querying, transformation, and performance tuning. Deep experience with cloud platforms , preferably AWS (e.g., S3, Glue, Redshift, Athena, EMR, Lambda). Experience with Azure or GCP is a plus. Experience building and managing data lakes and data warehouses. Strong understanding of distributed systems and big data More ❯

engineering standards and methodologies. Required Experience & Skills Proven experience as a Data Engineer with a strong focus on AWS cloud technologies. Proficiency in AWS services such as S3, Glue, Redshift, Lambda, Athena, EMR, and DynamoDB. Strong programming skills in Python and SQL. Experience with data modeling, ETL processes, and data warehousing concepts. Knowledge of infrastructure-as-code tools (e.g. More ❯

engineering standards and methodologies. Required Experience & Skills Proven experience as a Data Engineer with a strong focus on AWS cloud technologies. Proficiency in AWS services such as S3, Glue, Redshift, Lambda, Athena, EMR, and DynamoDB. Strong programming skills in Python and SQL. Experience with data modeling, ETL processes, and data warehousing concepts. Knowledge of infrastructure-as-code tools (e.g. More ❯

modular, efficient, and scalable data pipelines. Deep expertise in data modeling for both relational databases and data warehouses, including Star and Snowflake schema designs. Extensive experience working with AWS Redshift and Aurora for data warehousing and transactional workloads. Experience using dbt (Data Build Tool) for building modular, version-controlled, and testable data transformation workflows, with a strong understanding of More ❯

modular, efficient, and scalable data pipelines. Deep expertise in data modeling for both relational databases and data warehouses, including Star and Snowflake schema designs. Extensive experience working with AWS Redshift and Aurora for data warehousing and transactional workloads. Experience using dbt (Data Build Tool) for building modular, version-controlled, and testable data transformation workflows, with a strong understanding of More ❯

modular, efficient, and scalable data pipelines. Deep expertise in data modeling for both relational databases and data warehouses, including Star and Snowflake schema designs. Extensive experience working with AWS Redshift and Aurora for data warehousing and transactional workloads. Experience using dbt (Data Build Tool) for building modular, version-controlled, and testable data transformation workflows, with a strong understanding of More ❯

data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of data modeling More ❯

data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of data modeling More ❯

data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of data modeling 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 ❯

Engineers and Associates, and lead technical discussions and design sessions. Key requirements: Must-Have: Strong experience with AWS services: Glue, Lambda, S3, Athena, Step Functions, EventBridge, EMR, EKS, RDS, Redshift, DynamoDB. Strong Python development skills. Proficient with Docker , containerization, and virtualization. Hands-on experience with CI/CD , especially GitLab CI. Solid experience with Infrastructure as Code (Terraform, CloudFormation More ❯

and asynchronous collaboration to deliver high-quality solutions. Contribute to the technical growth of the team through knowledge sharing, mentoring, and innovation. Technologies & Tools: AWS Cloud Services : EMR, Glue, Redshift, Kinesis, Lambda, DynamoDB Programming & Scripting : Java, Python, Scala, Spark, SQL API integrations, data extraction, and transformation workflows Experience with big data processing, analytics, and scalable architectures Qualifications & Skills: Strong More ❯

and asynchronous collaboration to deliver high-quality solutions. Contribute to the technical growth of the team through knowledge sharing, mentoring, and innovation. Technologies & Tools: AWS Cloud Services : EMR, Glue, Redshift, Kinesis, Lambda, DynamoDB Programming & Scripting : Java, Python, Scala, Spark, SQL API integrations, data extraction, and transformation workflows Experience with big data processing, analytics, and scalable architectures Qualifications & Skills: Strong More ❯

and asynchronous collaboration to deliver high-quality solutions. Contribute to the technical growth of the team through knowledge sharing, mentoring, and innovation. Technologies & Tools: AWS Cloud Services : EMR, Glue, Redshift, Kinesis, Lambda, DynamoDB Programming & Scripting : Java, Python, Scala, Spark, SQL API integrations, data extraction, and transformation workflows Experience with big data processing, analytics, and scalable architectures Qualifications & Skills: Strong More ❯

libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/TeamCity More ❯

libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/TeamCity More ❯

libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/TeamCity 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 ❯

acceptable) Working knowledge of SQL and data modelling concepts Experience with BI tools (e.g., Power BI, Looker, Tableau) Familiarity with cloud data platforms such as Snowflake, BigQuery, or AWS Redshift Understanding of modern data architecture and APIs Our Offer Flexi-Week and Work-Life Balance: We prioritise your mental health and wellbeing, offering you a flexible four-day Flexi More ❯

quality and reliability in the organization Qualifications Understanding of data engineering (including SQL , Python , Data Warehousing , ETL , Dimensional Modelling , Analytics ) Understanding of cloud data infrastructure elements, and ideally AWS (Redshift, Glue, Athena, S3) and understanding of existing governance frameworks of data quality and their dimensions (DAMA, GOV.UK, etc.) Experience in Exploratory Testing, automation experience, and time and attention management 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 ❯

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 ❯

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 ❯