1 to 25 of 408 Amazon Redshift Jobs

Amazon Redshift is one of the world's most popular fully managed cloud data warehouse. Tens of thousands of enterprise customers use Redshift to crunch through exabytes of data in the cloud to make business critical decisions every day. To stay ahead in such a mission critical setting, at Redshift, we must always re-invent ourselves … help shape the future of Redshift. We are actively hiring a talented Senior Software Engineer in the Query Processing team of Redshift. Query processing is at the heart of Redshift dataplane and is responsible for the massive parallel execution engine. Key job responsibilities As a Senior Software Development Engineer in Redshift, you will build systems that benefit Redshift … to help drive business decisions with your technical input. Work in a startup-like development environment, where you're always working on the most important stuff. About the team Amazon Redshift is a fully managed, AI powered, petabyte-scale cloud data warehouse service. Tens of thousands of customers today depend on Redshift to revolutionize their data analytics More ❯

Core Azure SQL and MSSQL server Deep understanding of Azure-native services for data engineering. Experience with Azure Key Vault, Azure Monitor, and RBAC. AWS: Experience with S3, Glue, Redshift, and Lambda. Familiarity with IAM, CloudWatch, and Athena. Experience with BigQuery, Cloud Storage, and Dataflow. Familiarity with Cloud Functions, IAM, and Vertex AI (optional). Experience in one or More ❯

engineering role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field ● Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Redshift, BigQuery or other big data solutions ● Experience in data modelling and tools such as dbt, ETL processes, and data warehousing ● Experience with at least one of the programming languages More ❯

engineering role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field ● Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Redshift, BigQuery or other big data solutions ● Experience in data modelling and tools such as dbt, ETL processes, and data warehousing ● Experience with at least one of the programming languages More ❯

experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes and data More ❯

experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes and data More ❯

innovation and technical excellence. Your Profile Essential skills/knowledge/experience: Deep hands-on experience with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks More ❯

innovation and technical excellence. Your Profile Essential skills/knowledge/experience: Deep hands-on experience with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks More ❯

experience in ETL development and data engineering. Hands-on experience with Snowflake including data modeling, performance tuning, and SQL scripting. Proficiency in AWS services such as S3, Lambda, Glue, Redshift, and CloudWatch. Strong programming skills in Python or Scala for data processing. Experience with orchestration tools like Apache Airflow or AWS Step Functions. Familiarity with version control systems (e.g. 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 ❯

big data processing frameworks (e.g., Spark, Flink). Strong experience with cloud platforms (AWS, Azure, GCP) and related data services. Hands-on experience with data warehousing tools (e.g., Snowflake, Redshift, BigQuery), Databricks running on multiple cloud platforms (AWS, Azure and GCP) and data lake technologies (e.g., S3, ADLS, HDFS). Expertise in containerization and orchestration tools like Docker and More ❯

CD pipelines for data solutions Solid experience with cloud platforms (e.g., AWS, Azure, or GCP), and their data services. Deep understanding of data warehousing concepts and technologies (e.g., Snowflake, Redshift). Strong knowledge of ETL/ELT processes and tools. Solid experience of utilising PowerBI or similar visualisation tools Experience working with big data technologies and frameworks (e.g., Spark More ❯

CD pipelines for data solutions Solid experience with cloud platforms (e.g., AWS, Azure, or GCP), and their data services. Deep understanding of data warehousing concepts and technologies (e.g., Snowflake, Redshift). Strong knowledge of ETL/ELT processes and tools. Solid experience of utilising PowerBI or similar visualisation tools Experience working with big data technologies and frameworks (e.g., Spark More ❯

ELT processes, automation Technical Requirements: - Strong proficiency in SQL and Python programming - Extensive experience with data modeling and data warehouse concepts - Advanced knowledge of AWS data services, including: S3, Redshift, AWS Glue, AWS Lambda - Experience with Infrastructure as Code using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required Skills 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 ❯

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 ❯

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 ❯

data engineering experience , including at least 2 years hands-on with modern data platforms. Strong proficiency in SQL , data modelling, and query optimisation. Practical experience with Snowflake, Databricks, AWS Redshift, or Microsoft Fabric . Solid understanding of ETL/ELT pipelines and data warehousing principles . Strong communication and problem-solving skills. Ability to work both independently and collaboratively More ❯

data engineering experience , including at least 2 years hands-on with modern data platforms. Strong proficiency in SQL , data modelling, and query optimisation. Practical experience with Snowflake, Databricks, AWS Redshift, or Microsoft Fabric . Solid understanding of ETL/ELT pipelines and data warehousing principles . Strong communication and problem-solving skills. Ability to work both independently and collaboratively More ❯

to minimise disruption. Collaborate with various teams to align migration processes with organisational goals and regulatory standards. Proficiency in AWS ETL technologies, including Glue, Data Sync, DMS, Step Functions, Redshift, DynamoDB, Athena, Lambda, RDS, EC2 and S3 Datalake, CloudWatch for building and optimizing ETL pipelines and data migration workflows. Working knowledge of Azure data engineering tools, including ADF (Azure More ❯

using a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience More ❯

using a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience 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 ❯