Information Technology_USA - USA_Business Analyst

Real Soft•Jacksonville, FL

5d•Onsite

About The Position

Experienced Data Quality Engineer/Lead to design, implement, and operationalize enterprise-wide Data Quality capabilities leveraging DQLabs and modern cloud data platforms. The candidate will drive data profiling, DQ rule implementation, data observability, stewardship workflows, metadata management, and executive reporting to improve trust, compliance, and business decision-making. The role will partner closely with business stakeholders, data stewards, architects, and engineering teams across multiple insurance data domains.

Requirements

7+ years of Data Quality, Data Governance, or Data Management experience.
Strong understanding of CDEs, Business Glossary, Data Lineage, Metadata Management, and Data Stewardship.
Experience implementing enterprise Data Quality programs.
Knowledge of Data Quality dimensions and measurement frameworks.
Hands-on experience in DQLabs
Hands-on experience in DQ Tools
Hands-on experience in Collibra
Hands-on experience in Informatica

Nice To Haves

Insurance Brokerage domain experience

Responsibilities

Implement and administer DQLabs Data Quality platform and related data observability capabilities.
Profile source systems and identify Critical Data Elements (CDEs).
Define, configure, and maintain data quality rules for Completeness, Accuracy, Consistency, Validity, Timeliness, and Uniqueness.
Develop metadata-driven Data Quality frameworks and scorecards.
Build DQ dashboards and executive reporting for business and technology stakeholders.
Analyze data quality issues and drive remediation with business and application teams.
Establish Data Quality SLAs, thresholds, ownership, and governance processes.
Integrate DQ monitoring with Data Governance and Metadata Management platforms.
Support audit, compliance, regulatory, and reporting requirements.
Create quality trend reports, root cause analyses, and continuous improvement plans.
Collaborate with Data Stewards, Data Owners, Architects, and Analysts to improve enterprise data quality.
Define stewardship responsibilities, escalation paths, ownership models, and issue resolution workflows.