MS SQL Architect

INTELLISWIFT INC; Saint Paul (MN); On-site; USD 80,000 - 95,000; Full time

Job summary

A technology consulting firm is seeking a Senior Business Analyst in Saint Paul, MN, for a 6-month project to enhance and maintain an interagency data warehouse used for educational research. The successful candidate will manage data logistics, conduct data profiling, define data linking rules, and develop database architecture. Strong experience in data management and integration is essential for this impactful role supporting workforce employment data.

Qualifications

• Proven experience in managing data logistics and coordination.
• Ability to conduct rigorous data profiling and cleaning.
• Experience with data linking and integrating new data sets.

Responsibilities

• Coordinate and manage data set logistics and access issues.
• Conduct data profiling per MN P20W standards.
• Define data linking rules to improve quality.
• Develop program logic to link and load data.
• Create database architecture for new data storage.

Skills

Data management

Data profiling

Database architecture

Data integration

Job description

Job Role: Job Role: Senior Business Analyst

Location: Saint Paul, MN

Duration: 6 Months+

Enhance and maintain an interagency data warehouse. The interagency warehouse contains anonymized unit record data for individuals from birth to workforce employment that will support education research.

• Coordinate and manage data set “logistics” (e.g. issues, access to data, coordination of subject matter experts, etc.).
• Conduct data profiling, using MN P20W standards practices to iteratively work with the data provider to define, document, and clean the data.
• Define the data linking rules to be exercised on the personally identifying information available in each data set. Use this definition to evaluate existing data linking rules and integrate the new data set in a way that maintains or improves the quality of data linking results.
• Develop the program logic to link and load each data set into the operational data store (ODS).
• Create the database architecture required to support the linking, loading, and storage of the new data in the ODS, consistent with the existing architecture.
• Create and populate a data warehouse from the ODS.
• Evaluate and possibly refine the data operations to accommodate the data frequency and business needs.