1 to 25 of 53 Remote Permanent Amazon Redshift Jobs

Engineering with strong Python and SQL skills. Background in building and maintaining ETL/ELT pipelines in a cloud environment (AWS or Azure). Knowledge of data warehousing (e.g., Redshift, Postgres) and tools like DBT . Familiarity with CI/CD , data modelling, and Agile practices. Comfortable collaborating with Data Scientists and translating business needs into technical solutions. Experience 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. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem 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. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem 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. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem More ❯

Key Skills & Experience: Proven experience as a Senior Data Engineer in a large-scale or complex environment. Strong hands-on expertise with AWS data services (e.g., S3, Glue, Lambda, Redshift, Athena, EMR). Experience building data lakes and modern data platforms from the ground up. Proficiency with Python, SQL, and orchestration tools such as Airflow or dbt. Strong understanding More ❯

ll Bring Proven experience in data engineering, with a strong track record building AWS cloud data pipelines and data warehouses. Solid understanding of AWS services such as S3 and Redshift, particularly around storage, computation and security. Familiarity with modern BI tools such as Power BI or AWS QuickSight. Experience with open-source data stack tools like Airflow, DBT, Airbyte More ❯

ll Bring Proven experience in data engineering, with a strong track record building AWS cloud data pipelines and data warehouses. Solid understanding of AWS services such as S3 and Redshift, particularly around storage, computation and security. Familiarity with modern BI tools such as Power BI or AWS QuickSight. Experience with open-source data stack tools like Airflow, DBT, Airbyte More ❯

ll Bring Proven experience in data engineering, with a strong track record building AWS cloud data pipelines and data warehouses. Solid understanding of AWS services such as S3 and Redshift, particularly around storage, computation and security. Familiarity with modern BI tools such as Power BI or AWS QuickSight. Experience with open-source data stack tools like Airflow, DBT, Airbyte More ❯

ll Bring Proven experience in data engineering, with a strong track record building AWS cloud data pipelines and data warehouses. Solid understanding of AWS services such as S3 and Redshift, particularly around storage, computation and security. Familiarity with modern BI tools such as Power BI or AWS QuickSight. Experience with open-source data stack tools like Airflow, DBT, Airbyte More ❯

ll Bring Proven experience in data engineering, with a strong track record building AWS cloud data pipelines and data warehouses. Solid understanding of AWS services such as S3 and Redshift, particularly around storage, computation and security. Familiarity with modern BI tools such as Power BI or AWS QuickSight. Experience with open-source data stack tools like Airflow, DBT, Airbyte More ❯

Solution Architect, or Senior Data Engineer in a cloud environment (preferably AWS). Expertise in data modelling (Dimensional, Data Vault, Enterprise). Strong knowledge of AWS data services (S3, Redshift, Glue, Kinesis, Lambda, etc.). Experience in Data Strategy and Data Governance Strong communication and stakeholder management skills. The Nice-to-Haves (bonus points if you have these!): Experience 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 ❯

seamless data processing and analytics. Hands-on experience in data integration , including designing and optimising data pipelines (batch and streaming) and integrating cloud-based platforms (e.g., Azure Synapse, AWS Redshift, Google BigQuery ) with legacy systems, ensuring performance and scalability. Deep knowledge of ETL/ELT processes , leveraging tools like Apache Airflow, dbt, or Informatica , with a focus on ensuring More ❯

Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. 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 ❯

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 ❯

and eventual consistency systems using Kafka, .Net, Java, REST APIs, AWS, Terraform and DevOps Nice to have:experience in data pipping and modelling using SQL, DBT, ETL, Data Warehousing, Redshift and Python, and ecommerce and mobile applications background Additional Information Were a community here that cares as much about your life outside work as how you feel when youre More ❯

Engineering projects Strong experience in Python/PySpark, Databricks & Apache Spark Hands on experience with both batch & streaming pipelines Strong experience in AWS and associated tooling (Eg, S3, Glue, Redshift, Lambda, Terraform etc) Experience designing Data Engineering platforms from scratch Alongside their commitment to work-life balance the business also has an extremely competitive benefits package including, but not More ❯

Engineering projects Strong experience in Python/PySpark, Databricks & Apache Spark Hands on experience with both batch & streaming pipelines Strong experience in AWS and associated tooling (Eg, S3, Glue, Redshift, Lambda, Terraform etc) Experience designing Data Engineering platforms from scratch Alongside their commitment to work-life balance the business also has an extremely competitive benefits package including, but not More ❯

Engineering projects Strong experience in Python/PySpark, Databricks & Apache Spark Hands on experience with both batch & streaming pipelines Strong experience in AWS and associated tooling (Eg, S3, Glue, Redshift, Lambda, Terraform etc) Experience designing Data Engineering platforms from scratch Alongside their commitment to work-life balance the business also has an extremely competitive benefits package including, but not More ❯

Engineering projects Strong experience in Python/PySpark, Databricks & Apache Spark Hands on experience with both batch & streaming pipelines Strong experience in AWS and associated tooling (Eg, S3, Glue, Redshift, Lambda, Terraform etc) Experience designing Data Engineering platforms from scratch Alongside their commitment to work-life balance the business also has an extremely competitive benefits package including, but not More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯