The incumbent serves as the Data and ETL architect on the Health Sciences Data Warehouse (HSDW) team. They are responsible for ensuring the data and ETL architecture supports stakeholder requirements related to the HSDW project. They will work with the HSDW team to design and develop data architecture (physical and/or logical) and ETL standards and develop ETL.
As part of driving key architectural decisions related to data, ETL and reporting within the data warehousing environment, the position will also develop, implement and enforce strategies to optimize data quality, ETL development and test strategies for the data warehouse. They will be responsible for developing and maintaining documentation and specifications for the Data Warehouse in their areas of responsibility.
The incumbent will also be engaged in ETL development, testing, and supporting existing ETL. This will include, but not limited to implementation of data integration strategies per ETL specifications and iTarget standards. They will lead discussions regarding architectural components that comprise the environment itself and participate in modeling sessions to understand business rules associated with data transformation. The incumbent will work on developing and implementing test strategies such as unit testing of ETL transformations and integration testing of ETL jobs.
A strong understanding of Data Architecture, ETL Architecture, ETL concepts and Data warehousing tools is required. Familiarity with Pentaho and Oracle business Intelligence (OBIEE) is preferred. A strong discipline in creating appropriate documentation and specifications is required.
The University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity and diversity. EEO/AA/M/F/Vets/Disabled
Master's degree in a technology-related field and 3-5 years experience, or equivalent, required.Thorough knowledge of Data Warehouse concepts and experience developing ETL. Thorough understanding of all aspects/challenges regarding moving data from source to target. A strong understanding of Data Architecture, ETL Architecture, ETL concepts and Data warehousing tools is required. Familiarity with Pentaho, OBIEE and Oracle is preferred. A strong discipline in creating appropriate documentation and specifications is required.