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# Data Quality Specialist

- **Company:** TEKSYSTEMS INC.
- **Location:** Omaha, NE, United States (Remote available)
- **Experience:** Expert
- **Salary:** $114,400.0 - $135,200.0
- **Contract:** Temporary contract
- **Skills:** Business Analytics Applications, Data Analysis, Cloud Computing, Data Validation, Data Governance, Data Integration, Data Profiling, Database Testing, Digital Assets, Metadata, SQL Databases, Test Data, Azure Data Factory, Snowflake, Microsoft Fabric, Data Management, Databricks
- **Published:** August 31, 2026
- **Apply:** https://www.dice.com/job-detail/c668749a-6b73-425a-834e-721747129691

## About the Role

7+ years of progressive experience in data quality, data analysis, data testing, data governance, data management, business intelligence, data integration, or related disciplines.
Demonstrated experience facilitating stakeholder discussions to define data quality rules, critical data elements, metrics, thresholds, and acceptance criteria.
Strong hands-on experience with data profiling, SQL-based analysis, data validation, source to target testing, reconciliation, and root cause analysis.
Deep understanding of data quality traits, including completeness, accuracy, validity, consistency, uniqueness, conformity, timeliness, and integrity.
Experience designing or implementing data quality frameworks, rule libraries, scorecards, dashboards, monitoring, and exception management processes.
Working knowledge of data governance, metadata, lineage, business glossaries, data stewardship, and data issue management operating models.
Proficiency with SQL and experience working with cloud lakehouse, warehouse, or analytics platforms such as Databricks, Snowflake, Microsoft Fabric, Azure data services, or comparable technologies.
Strong facilitation, written communication, analytical, and stakeholder management skills.

## Description

Seeking a Data Quality Analyst to establish and advance data quality practices that support trusted, reusable data assets across lakehouse, integration, reporting, and operational environments. This hands-on role partners with business stakeholders, data stewards, architects, and engineers to define data quality rules and metrics; profile and test data; identify root causes; and implement sustainable quality controls.


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