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Moderate due to recognizable RegTech brand and general data role but niche DQ skills and non-metro location.
Medium because DQ and SQL skills transfer across industries, but regulatory and financial domain experience is preferred.
Medium because explicit SQL, SSIS, and controlled-correction expertise required despite no hard years threshold.
Ensure accurate, complete, and reliable data underpinning CUBE’s regulatory intelligence product through data profiling, quality rule design, and monitoring scorecards.
Investigate and resolve data quality issues including root cause analysis, controlled corrections, and remediation across MSSQL databases and ETL pipelines in compliance with governance and audit requirements.
Collaborate across technology, product, operations, and compliance teams to implement data ingestion improvements, support AI-enabled monitoring tools, and maintain documentation aligned with regulatory standards.
Experience in data quality, data operations, or BI/MDM environments; financial services experience advantageous.
Hands-on proficiency with MS SQL Server including DDL/DML/TCL commands, advanced Excel, and experience with SSIS or similar ETL tools.
Relevant degree in data, IT, business, or related field or equivalent experience.
Knowledge of data governance principles and data quality tooling; certifications (e.g., DAMA/CDMP, Microsoft) are a plus.
Analytical professional skilled in SQL and ETL workflows who can independently identify, triage, and remediate data issues to improve data quality metrics.
Experienced in working under data governance and regulatory compliance frameworks, capable of maintaining traceability and audit-ready documentation.
Comfortable adopting AI-enabled tools for monitoring and automation to increase efficiency and data accuracy.