1 to 25 of 95 Amazon Redshift Jobs in the South East

AWS) Cloud Proficiency: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its core data services (e.g., S3, Redshift, Lambda/Functions, Glue). Data Modelling: Deep understanding of ELT/ETL patterns, and data modelling techniques. CRM/Customer Data Focus: Experience More ❯

AWS) Cloud Proficiency: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its core data services (e.g., S3, Redshift, Lambda/Functions, Glue). Data Modelling: Deep understanding of ELT/ETL patterns, and data modelling techniques. CRM/Customer Data Focus: Experience More ❯

AWS) Cloud Proficiency: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its core data services (e.g., S3, Redshift, Lambda/Functions, Glue). Data Modelling: Deep understanding of ELT/ETL patterns, and data modelling techniques. CRM/Customer Data Focus: Experience More ❯

AWS) Cloud Proficiency: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its core data services (e.g., S3, Redshift, Lambda/Functions, Glue). Data Modelling: Deep understanding of ELT/ETL patterns, and data modelling techniques. CRM/Customer Data Focus: Experience More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

a focus on backend, API, and data systems using tools like Pytest and Postman. Expertise in Pandas, SQL, and AWS analytics services (Glue, Athena, Redshift) for data profiling, transformation, and validation within data lakes. Solid experience with AWS (S3, Lambda, EMR, ECS/EKS, CloudFormation/Terraform) and understanding More ❯

technologies (e.g., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Google Cloud and cloud-based data services (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery). Experience with DataOps practices and tools, including CI/CD for data pipelines. Excellent leadership, communication, and interpersonal More ❯

technologies (e.g., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Google Cloud and cloud-based data services (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery). Experience with DataOps practices and tools, including CI/CD for data pipelines. Excellent leadership, communication, and interpersonal More ❯

optimization, and stored procedures. Strong coding skills in Python for data transformation, scripting, and automation. Experience with cloud platforms such as AWS (e.g., S3, Redshift, Lambda) , Azure (e.g., Data Factory, Synapse) , or GCP (e.g., BigQuery, Cloud Functions) . Familiarity with data orchestration tools (e.g., Airflow, dbt) and version control More ❯

optimization, and stored procedures. Strong coding skills in Python for data transformation, scripting, and automation. Experience with cloud platforms such as AWS (e.g., S3, Redshift, Lambda) , Azure (e.g., Data Factory, Synapse) , or GCP (e.g., BigQuery, Cloud Functions) . Familiarity with data orchestration tools (e.g., Airflow, dbt) and version control More ❯

optimization, and stored procedures. Strong coding skills in Python for data transformation, scripting, and automation. Experience with cloud platforms such as AWS (e.g., S3, Redshift, Lambda) , Azure (e.g., Data Factory, Synapse) , or GCP (e.g., BigQuery, Cloud Functions) . Familiarity with data orchestration tools (e.g., Airflow, dbt) and version control More ❯

a similar role. Proficiency in SQL and/or Python for data transformation and automation. Hands-on experience with cloud data warehouses (e.g. Snowflake, Redshift, BigQuery). Strong understanding of data modelling, ETL/ELT workflows, and data validation. Experience with BI tools such as Power BI, Tableau, or More ❯

business understands and serves its customers. What You’ll Bring 5+ years in data engineering Deep Python and SQL expertise Strong command of AWS (Redshift, S3, EC2, Lambda) Proven Kafka and streaming experience Solid ETL pipeline and API integration skills Confident working with data governance and security Able to More ❯

business understands and serves its customers. What You’ll Bring 5+ years in data engineering Deep Python and SQL expertise Strong command of AWS (Redshift, S3, EC2, Lambda) Proven Kafka and streaming experience Solid ETL pipeline and API integration skills Confident working with data governance and security Able to More ❯

business understands and serves its customers. What You’ll Bring 5+ years in data engineering Deep Python and SQL expertise Strong command of AWS (Redshift, S3, EC2, Lambda) Proven Kafka and streaming experience Solid ETL pipeline and API integration skills Confident working with data governance and security Able to More ❯

physical). • Proficiency in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra). • In-depth knowledge of data warehousing concepts and tools (e.g., Redshift, Snowflake, Google BigQuery). • Experience with big data platforms (e.g., Hadoop, Spark, Kafka). • Familiarity with cloud-based data platforms and services (e.g., AWS More ❯

physical). • Proficiency in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra). • In-depth knowledge of data warehousing concepts and tools (e.g., Redshift, Snowflake, Google BigQuery). • Experience with big data platforms (e.g., Hadoop, Spark, Kafka). • Familiarity with cloud-based data platforms and services (e.g., AWS More ❯

AWS. Collaborate with engineering teams to ensure a smooth transition and system stability. Languages & Scripting: Python (primary scripting language for Lambda functions) SQL (BigQuery, Redshift) R (not essential but beneficial for interpreting existing scripts) Cloud & Infrastructure: AWS services including Lambda, API Gateway, S3, CloudWatch, Kinesis Firehose Terraform for infrastructure More ❯

AWS. Collaborate with engineering teams to ensure a smooth transition and system stability. Languages & Scripting: Python (primary scripting language for Lambda functions) SQL (BigQuery, Redshift) R (not essential but beneficial for interpreting existing scripts) Cloud & Infrastructure: AWS services including Lambda, API Gateway, S3, CloudWatch, Kinesis Firehose Terraform for infrastructure More ❯

management Experience required: Experience in building and scaling BI and Data Architecture Expertise in modern BI and Data DW platforms such as Snowflake, BigQuery, Redshift, Power BI etc Background in ETL/ELT tooling and Data Pipelines such as DBT, Fivetran, Airflow Experienced in Cloud based solutions (Azure, AWS More ❯

management Experience required: Experience in building and scaling BI and Data Architecture Expertise in modern BI and Data DW platforms such as Snowflake, BigQuery, Redshift, Power BI etc Background in ETL/ELT tooling and Data Pipelines such as DBT, Fivetran, Airflow Experienced in Cloud based solutions (Azure, AWS More ❯

data transformation and modeling in a modern data stack. Proficiency in SQL , Python , and PySpark . Experience with AWS services such as S3, Athena, Redshift, Lambda, and CloudWatch. Familiarity with data warehousing concepts and modern data stack architectures. Experience with CI/CD pipelines and version control (e.g., Git More ❯

data transformation and modeling in a modern data stack. Proficiency in SQL , Python , and PySpark . Experience with AWS services such as S3, Athena, Redshift, Lambda, and CloudWatch. Familiarity with data warehousing concepts and modern data stack architectures. Experience with CI/CD pipelines and version control (e.g., Git More ❯