MS SQL Architect

Jobsbridge

Saint Paul (MN)

On-site

USD 70,000 - 90,000

Full time

14 days+
Application generator

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Job summary

A data management company in Minnesota is seeking a candidate to coordinate and manage logistics for data sets. Responsibilities include conducting data profiling, defining data linking rules, and developing program logic to link and load data into an operational data store. The ideal candidate should have experience in data management, knowledge of database architecture, and familiarity with data warehousing practices. This role offers an opportunity to significantly contribute to data quality and organization.

Qualifications

  • Experience in data management and logistics.
  • Familiarity with data profiling techniques.
  • Knowledge of database architecture and data warehousing.

Responsibilities

  • Coordinate and manage data set logistics.
  • Conduct data profiling to clean and document data.
  • Define data linking rules for personally identifying information.
  • Develop program logic to link and load data into the ODS.
  • Create database architecture for linking and loading data.
  • Create and populate a data warehouse from the ODS.
  • Evaluate and refine data operations based on business needs.

Job description

• 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

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