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# Data Warehouse Analyst II - WI

- **Company:** Shiro Technologies
- **Location:** Wisconsin Dells, WI, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Profiling, Databases, Data Architecture, Data Cleansing, Data Profiling, Data Warehousing, IBM DB2, Database Design, Python (Programming Language), Metadata, Microsoft SQL Server, Oracle Databases, Oracle SQL Developer, Oracle Warehouse Builder, SQL Databases, Data Management
- **Published:** August 11, 2026
- **Apply:** https://www.dice.com/job-detail/899defcf-b9d0-4cc6-a504-941550a5fff5

## About the Role

5+ years of experience in Data Profiling.

3+ years of experience with Python.

5+ years of experience with database design concepts.

5+ years of experience creating and reviewing SQL scripts.

5+ years of experience with Oracle PL/SQL.

5+ years of experience with metadata tools.

5+ years of experience with Oracle 11g, DB2, and/or SQL Server.

4+ years of experience with Oracle Data Dictionary views.

5+ years of experience with metadata documentation.

5+ years of experience in data quality assessment and profiling.

Excellent organizational, analytical, and communication skills.

Location Requirement: Candidate must be a Wisconsin resident or willing to relocate to Wisconsin within 30 days of the start date at their own expense. The position is expected to be 90-100% remote, but onsite work may occasionally be required with sufficient notice.

## Description

We are seeking an experienced Data Warehouse Analyst II responsible for assessing data quality and metadata within a data architecture environment. The candidate will perform data profiling, analysis, documentation, and recommend improvements to data quality and data management processes., Audit existing databases to assess completeness, accuracy, outliers, duplicates, and other data characteristics.

Investigate and define automated validation rules to ensure data accuracy and identify errors at the point of entry.

Develop data cleansing and remediation recommendations for data irregularities.

Establish KPIs to measure data health and build reporting dashboards to track quality metrics and trends.

Investigate recurring data errors, including system bugs, user errors, and integration issues, and recommend systemic solutions.

Document and define key metadata related to database architecture.

Make recommendations regarding data maintenance and data quality.

Collaborate with Data Modelers and Data Architects on data management and data quality initiatives.


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