Top skills:
- Advanced knowledge of conceptual, logical and physical data modeling concepts; looking for BOTH APPLICATION and data warehouse database modeling experience (5+ years).
- Experience in ERWIN data modeling software (5+ years).
- Experience in reverse-engineering data structures and metadata development. (5+ years).
- Advanced experience in Oracle PL/SQL (6+ years).
Preferred skill:
Experience with human services.
Interview process: via Zoom/Teams.
Onsite, hybrid or remote: WI residency required. Must be WI resident or willing to relocate within 30 days of start date at own expense. 90-100% remote but can require staff to come onsite as necessary with sufficient notice. Onsite work is not likely, but candidate should be prepared to come onsite in Madison, WI if required.
Duration: The project is currently funded through 12/31/26 with the potential for an extension.
Project details: Position will be responsible for documenting key metadata on current production application databases. Position will work independently to assess and create key metadata documentation with guidance from senior Data Architect. While this is being posted as a Business Intelligence Data Modeler, the organization is looking for someone with both application and data warehouse database modeling experience.
The individual in this position will:
- Develop conceptual, logical, and physical data models for DCF data architecture. Ensure that all relevant aspects of data model (granularity, etc.) are considered. Analyze the logical and physical database models and guarantee models are in accordance with standards.
- Document and define key metadata around database architecture.
- Translate technical aspects of data modeling (facts, dimensions, “snowflaking”, etc.) into language that non-technical users can understand. Work with both technologists as well as non-technical users with ease and approachability.
- Make recommendations on data maintenance tactics for slowly changing dimensions, data roll-off / archival planning, etc.
- Design models optimized for both storage (warehouse) and query / retrieval (end user marts). Perform analysis and testing of relational databases and investigate any data load failures or data retrieval issues.
- Assessment of data quality within database architecture.
** The project is currently funded through 12/31/26 with the potential for an extension.”