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# Technical Data Analyst

- **Company:** Resourcesoft, Inc.
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Customer Data Management, Data Validation, Data Deduplication, Extract Transform Load (ETL), Data Mapping, Data Migration, Data Profiling, Executive Information Systems, Python (Programming Language), Windows PowerShell, Power BI, Salesforce.Com, SQL Databases, Systems Integration, Tableau (Software), Enterprise Data Management, Scripting, Restful APIs, Api Management, Mulesoft
- **Published:** July 31, 2026
- **Apply:** https://www.dice.com/job-detail/883fe036-ae24-469a-b037-ae606fc34667

## About the Role

* 5 or more years of experience in enterprise data analysis and data quality management.
 * Proficiency in SQL programming and scripting utilizing Python or PowerShell for data automation.
 * Experience with developing interactive executive dashboards utilizing Tableau and Microsoft Power BI.
 * Experience in API-led integrations and enterprise data exchange utilizing MuleSoft.
 * Experience with executing data profiling, cleansing, and deduplication methodologies utilizing ETL tools.
 * Experience in supporting enterprise CRM data migrations and integrations targeting Salesforce platforms.
 * Excellent verbal and written communication skills to present data quality metrics to stakeholders.

## Description

* Program robust SQL queries and Python scripts to automate complex data reconciliation processes.
 * Architect and execute automated data validation routines to compare source and target enterprise datasets.
 * Cleanse, standardize, and deduplicate massive datasets to ensure optimal enterprise data quality.
 * Design interactive Tableau and Power BI dashboards to track data migration progress and operational KPIs.
 * Develop comprehensive data mapping documents and conversion templates to support large-scale migrations.
 * Implement and troubleshoot API integrations utilizing MuleSoft and RESTful web services.
 * Evaluate enterprise data models to identify gaps, inconsistencies, and structural validation anomalies.


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