

Signify Technology
DOMO Migration Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Domo Migration Engineer, a 3-month remote contract position. Key skills include ETL, SQL, Amazon Redshift, and data transformation. Experience with BI migrations and user acceptance testing is essential. Immediate start required.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
November 21, 2025
π - Duration
3 to 6 months
-
ποΈ - Location
Remote
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Chicago, IL
-
π§ - Skills detailed
#SQL Server #JDBC (Java Database Connectivity) #Redshift #SQL (Structured Query Language) #Data Lineage #ODBC (Open Database Connectivity) #Migration #Security #UAT (User Acceptance Testing) #Documentation #Dataflow #"ETL (Extract #Transform #Load)" #Amazon Redshift #Data Access #BI (Business Intelligence) #Data Transformations #Data Pipeline #Datasets
Role description
USA contract remote role
3 months duration
asap start
eeking an experienced Domo professional to support a major BI migration from an existing SQL Server environment to Amazon Redshift. This role focuses on rebuilding datasets, refactoring data transformations, validating dashboard accuracy, and ensuring a seamless cutover for business users with no interruption in reporting, security, or data accessibility.
Key Responsibilities
β’ Rebuild Domo datasets to source data from Redshift using ODBC/JDBC connections, Workbench configurations, and federated query options while preserving scheduling, row-level security, and governance controls.
β’ Configure and optimize Redshift federated connections in Domo, including authentication, data pipelines, refresh cadence, and dependency orchestration.
β’ Refactor Magic ETL, DataFlows, DataFusion logic, and Beast Mode calculations to align with new warehouse structures, data models, and transformation conventions.
β’ Recreate and validate row-level access policies (PDP) so that authorized audiences retain correct filtered visibility after migration.
β’ Perform full dashboard parity checksβincluding KPIs, filters, drill paths, alerts, and visual layoutsβto confirm the Redshift-backed versions match the legacy system.
β’ Identify, document, and resolve discrepancies by collaborating with engineering and analytical stakeholders.
β’ Improve dashboard performance through tuning methods such as caching strategies, optimized dataflows, and partitioned dataset designs.
β’ Manage a structured migration tracker covering approximately 150 datasets and 50 dashboards, including status, validation evidence, issue logs, and sign-off checkpoints.
β’ Facilitate user acceptance testing, gather feedback, and deliver clear cutover documentation such as data lineage, support instructions, and release notes.
USA contract remote role
3 months duration
asap start
eeking an experienced Domo professional to support a major BI migration from an existing SQL Server environment to Amazon Redshift. This role focuses on rebuilding datasets, refactoring data transformations, validating dashboard accuracy, and ensuring a seamless cutover for business users with no interruption in reporting, security, or data accessibility.
Key Responsibilities
β’ Rebuild Domo datasets to source data from Redshift using ODBC/JDBC connections, Workbench configurations, and federated query options while preserving scheduling, row-level security, and governance controls.
β’ Configure and optimize Redshift federated connections in Domo, including authentication, data pipelines, refresh cadence, and dependency orchestration.
β’ Refactor Magic ETL, DataFlows, DataFusion logic, and Beast Mode calculations to align with new warehouse structures, data models, and transformation conventions.
β’ Recreate and validate row-level access policies (PDP) so that authorized audiences retain correct filtered visibility after migration.
β’ Perform full dashboard parity checksβincluding KPIs, filters, drill paths, alerts, and visual layoutsβto confirm the Redshift-backed versions match the legacy system.
β’ Identify, document, and resolve discrepancies by collaborating with engineering and analytical stakeholders.
β’ Improve dashboard performance through tuning methods such as caching strategies, optimized dataflows, and partitioned dataset designs.
β’ Manage a structured migration tracker covering approximately 150 datasets and 50 dashboards, including status, validation evidence, issue logs, and sign-off checkpoints.
β’ Facilitate user acceptance testing, gather feedback, and deliver clear cutover documentation such as data lineage, support instructions, and release notes.






