Job Description

Job Summary:
The Data Integration and Warehouse Engineer develops, maintains, and troubleshoots data integrations, primarily in Informatica Cloud (IICS), and supports multiple database systems for the School of Medicine and Public Health. The person in this role works closely with our data analysts, developers, system administrators, and external partners to help direct the flow of data and ensure consistency for multiple needs. This includes consulting on and supporting the availability of this data to our data visualization platform, applications, websites, and other reporting projects. Strong candidates for this role will have a good technical foundation in building and optimizing data systems, a love of learning, and an ability to develop relationships across reporting lines. Excellent candidates will be able to adapt their communication style for collaboration with technical colleagues, diverse subject matter experts, and leadership, and are excited by what a stable data ecosystem can enable.

The person in this role has primary responsibility for authoring and maintaining ETL/ELT mappings, mapping tasks, and workflows from a wide variety of sources. New or extended data models and integrations are established through working with subject matter experts and key stakeholders to acquire functional domain knowledge and understand evolving business needs. This data integration work includes support of projects addressing data quality issues.

In the data warehouse, this person monitors, responds to, and resolves existing database access and performance issues. This includes reviewing database objects, including views, triggers, stored procedures, and execution time to provide efficiency improvements, and optimizing via tablespace sizing and management. The person in this role will also assist in the initial setup and configuration of a new data warehouse as part of the UW-Madison transition to Workday in July 2025.

Collaboration is key. This person coordinates with System Operations for backups, patches, and upgrades, is expected to establish and maintain effective working relationships with data leaders and administrators from UW campus and UW Health, and collaborates across the breadth of SMPH IT.

The Data Integration and Warehouse Engineer will report to the Data & Analytics IT Director.

Responsibilities:
Technical Integration Engineer II (IT042)
Technical Integration Engineer III (IT043)
Institutional Statement on Diversity:
Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals.

The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background - people who as students, faculty, and staff serve Wisconsin and the world.

For more information on diversity and inclusion on campus, please visit: Diversity and Inclusion

Education:
Preferred
Associate's Degree

Qualifications:
Required:
- Experience in multi-system data integration
- Experience with data integration through extract, transform, load (ETL) & ELT patterns
- Experience with enterprise data integration tools (e.g., Informatica Intelligent Cloud Services (IICS) Data Integration, Informatica PowerCenter, dbt, etc), preferably IICS
- Experience with data warehouse development, maintenance, and auditing/logging

Preferred:
- Experience with structured and unstructured data
- Experience with data modeling and relational database design
- Experience with on-premise data storage (e.g., Oracle) and/or cloud data storage (e.g., Snowflake, Redshift)
- Experience with Finance and Human Resources data

Additionally required to be considered for level III:
- Demonstrated ability in mentoring colleagues in best practices regarding data use and data integrations
- Examples of a proactive approach to handling data integration issues