Business Intel Data Modeler-IV (Remote)
Madison, WI, WI
Contracted
Experienced
Job Title: Business Intel Data Modeler-IV (Remote)
Location: Madison, WI 53703
Duration: 06+ Months
Job Description:
The client is implementing the Enterprise Analytics
Platform (EAP), including a data lake with data serving the 13 UW universities and campuses.
The EAP team is seeking a data engineer with data modeling skills and expertise. The position will work closely with the analysts, developers, and consumers to design data models that support integration of multiple source systems into cohesive data reporting and visualization solutions.
Major Responsibilities:
Minimum Qualifications:
Top Skills & 3 Years of Experience:
Nice to Have:
Location: Madison, WI 53703
Duration: 06+ Months
Job Description:
The client is implementing the Enterprise Analytics
Platform (EAP), including a data lake with data serving the 13 UW universities and campuses.
The EAP team is seeking a data engineer with data modeling skills and expertise. The position will work closely with the analysts, developers, and consumers to design data models that support integration of multiple source systems into cohesive data reporting and visualization solutions.
Major Responsibilities:
- Create and maintain Enterprise Analytics Platform (EAP) data models that integrate multiple source systems into a coherent, cohesive catalog of data. Some of those source systems include Oracle/Peoplesoft HR and Finance and Workday.
- Design, develop and maintain conceptual, logical, and physical data models.
- Work with analyst team to review business requirements and assess the data model needs to best fulfill those requirements. Advise on exercises like gap analyses or cost/benefit/risk analyses.
- Ensure data models adhere to design and security standards.
- Perform data profiling and analysis to ensure the quality of the data models.
- Collaborate with functional and technical team to integrate model metadata with consumer tools (e.g. Collibra, Tableau).
- Collaborate with development team to ensure models are clear and comprehensive. Provide developers with model and/or data definition language (DDL).
- Support EAP customers/consumers with data model walkthroughs and help queue responses.
Minimum Qualifications:
- Minimum 3 years’ experience as a Data Architect, Data Scientist, Data Analyst, Data Engineer, Business Intelligence (BI) Analyst, or similar role.
- In-depth understanding of database structure principles.
- Thorough understanding of data modeling principles and best practices, including expertise in both relational and dimensional modeling, with a specific focus on the AWS Redshift database.
- Strong proficiency in data modeling tools, with expertise in ER Studio.
- In-depth understanding of data warehousing concepts, data lakes, and AWS cloud-based architecture.
- Strong understanding of the software development lifecycle (SDLC).
- Familiarity with metadata management principles.
- Strong understanding of master and reference data management principles.
- Strong understanding of object-oriented design or domain-driven design.
- Experience gathering and analyzing data, report, and business requirements.
- Experience working in a team environment.
- Ability to communicate effectively with users with varying levels of technical vocabulary.
- Analytical skills.
- Problem-solving attitude.
Top Skills & 3 Years of Experience:
- Experience as a Data Architect, Data Scientist, Data Analyst, Data Engineer, Business Intelligence (BI) Analyst, or similar role.
- Experience gathering and analyzing data, report, and business requirements.
- Understanding of data modeling principles and best practices, including expertise in both relational and dimensional modeling, with a specific focus on the AWS Redshift database.
Nice to Have:
- Experience with higher education data and reporting, e.g. students, human resources (HR), finance, operations.
- Experience in AWS cloud environment.
- Experience in agile and/or hybrid (agile and waterfall) teams.
- Experience migrating legacy applications and data systems to new environments.
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