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# Data Specialist

- **Company:** Cyma Systems Inc
- **Location:** Hartford, WI, United States
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Profiling, Data Validation, Data Control, Data Conversion, Data Masking, Data Structures, DataOps, SQL Databases, Data Analytics, Data Pipelines
- **Published:** August 7, 2026
- **Apply:** https://www.dice.com/job-detail/0de3e289-2ff7-4b45-9889-47316c8e971a

## About the Role

We are seeking an experienced and independent Data Specialist to join our team and support ongoing data operations alongside our existing US-based resource. The ideal candidate will be a self-starter with strong technical expertise in data analysis, data quality management, data modeling, and data masking, capable of working with minimal supervision while effectively coordinating with multiple stakeholder teams. Experience working on a mainframe and SQL will be helpful., * Proven, hands-on experience in data analysis, data quality management, data modeling, and data masking.

 * Strong understanding of data validation, standardization, and governance/control practices.
 * Demonstrated ability to work independently with minimal guidance or hand-holding.
 * Strong communication and coordination skills, with experience working across distributed/cross-functional teams (onshore/offshore).
 * Proficiency with relevant data tools and platforms (e.g., SQL, data quality/profiling tools, masking tools - specify per tech stack).
 * Prior experience supporting data conversion or migration projects is a plus.

## Description

1. Data Analysis
 * Analyze large and complex datasets to identify trends, patterns, anomalies, and actionable insights.
 * Support business and technical teams with data-driven recommendations.
 * Prepare clear, accurate reports and summaries of findings for stakeholders.

 2. Data Quality
 * Perform data quality assessments to identify gaps, inconsistencies, and errors.
 * Define and implement data quality rules, checks, and monitoring processes.
 * Collaborate with source teams to remediate data quality issues at the root cause.

 3. Data Modeling (Validation, Standardization, and Control)
 * Validate data models against business and technical requirements.
 * Standardize data structures, formats, and definitions across systems.
 * Establish and enforce data controls to ensure consistency, accuracy, and compliance.

 4. Data Masking
 * Apply data masking and anonymization techniques to protect sensitive and confidential information.
 * Ensure masking approaches comply with data privacy, security, and regulatory requirements.
 * Work with technical teams to implement masking within data pipelines and environments.

 5. Cross-Team Coordination
 * Serve as a liaison between App Dev, Data Conversion, and Client teams.
 * Facilitate clear communication, alignment, and issue resolution across teams.
 * Track dependencies, action items, and deliverables to ensure timely execution.


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