Data Conversion Lead

Job ID: NC-791876

Hybrid/Local Tax Data Conversion Lead (12+/in-person IV) with governance, legacy/mainframe migration/cleanup, Oracle/SQL Server, Erwin experience

Location: Raleigh, NC (NCDOR)
Duration: 12 Months
This is a hybrid position. The candidate will be working up to four days a week in the Raleigh office.
*In person interviews are required.

Skills:
Understanding of principles and practices of establishing governance models, data ownership frameworks, and alignment with PMO structures Required 5 Years
Understanding of strategies, methodologies, and tools for large-scale legacy-to-modern system conversions, including mainframe migrations. Required 5 Years
Ability to translate program-wide modernization objectives into a data conversion roadmap that supports business continuity Required 5 Years
Techniques for identifying invalid, inconsistent, orphaned, and incomplete data, along with remediation methods and root cause analysis. Required 5 Years
Expertise in Oracle, SQL Server, and Erwin Data Modeler, including Erwin Data Modeler implementation and use of the tool for generating documentation Required 5 Years
Knowledge of government tax/revenue operations and the specific challenges in modernizing these systems. Required 3 Years
Standards for cataloging enterprise data sources and maintaining metadata at database, table, and field levels. Required 5 Years
Methods for data reconciliation, validation, and iterative conversion testing within staging environments. Required 5 Years
Ability to resolve data ambiguities and conflicts across multiple legacy sources with accuracy and efficiency. Required 5 Years

Description:
The Data Conversion Lead is responsible for planning, coordinating, and executing data conversion activities in support of the Tax System Modernization Program.

Role Overview
The Data Conversion Lead is responsible for planning, coordinating, and executing data conversion activities in support of the Tax System Modernization Program. This role ensures that accurate, complete, and usable data is migrated from legacy systems into the modern COTS platform for each release. The Data Conversion Lead works closely with the Vendor Data Conversion Lead, Functional Owners, Functional SMEs, Tax Schedule SMEs, Database Administrators, System Architects, other Vendor staff, and testing teams to define data mapping rules, oversee extract and transformation processes, and validate the quality and readiness of converted data. This individual plays a critical role in enabling the retirement of legacy systems by ensuring that historical and operational data are properly prepared and transitioned to the modern environment.

Responsibilities
Develop and manage the overall data conversion strategy aligned to tax schedule release timelines.
In conjunction with Functional Owners, Functional SMEs, and Tax Schedule SMEs, validate converted data in the COTS system to ensure completeness, accuracy, and usability.
Coordinate with System Architects to align conversion activities with the overall technical architecture and data design.
Work with Database Administrators to stage, load, and monitor data migration activities.
Track, triage, and resolve data conversion defects and issues across all testing and production environments.
Support data readiness for training and UAT environments, ensuring that converted data is suitable for scenario execution.
Contribute to cutover planning and execution of production data conversion during each release go-live.
Maintain documentation of data mapping, conversion rules, trial results, and final outcomes for audit and knowledge transfer.
Provide status reporting and updates to program leadership, identifying risks, blockers, and mitigation plans related to data conversion.
Ensure compliance with agency data standards, security policies, and retention requirements throughout the conversion process.
Direct teams of business users and technical staff, ensuring alignment with program milestones and deliverables.
Adjust strategies to accommodate evolving program needs, new data discoveries, and vendor requirements over a multi-year program.
Lead the review, validation, and cataloging of all operational data sources, including shadow systems and spreadsheets.
Lead analysis of legacy system data to identify quality issues, inconsistencies, and transformation requirements.
Lead cross-functional working sessions with SMEs, technical staff, vendors, and stakeholders to define remediation approaches and resolve legacy system data-related issues.
Prioritize and lead data cleanup efforts of legacy system data.
Produce and maintain Data Dictionaries, quality review reports, remediation plans, and status reports for the TMO.
Collaborate with Functional Owners, Functional SMEs, Tax Schedule SMEs, and Vendor staff to define data mapping and transformation rules that reflect business and system requirements.
Oversee the design and execution of extract-transform-load (ETL) processes in coordination with DBAs and technical teams.
In conjunction with the Vendor Data Conversion Lead, coordinate and lead trial conversions and mock loads to identify issues and validate conversion logic.
Work with testing teams to ensure converted data supports test case execution and meets expected outcomes.

Participation
This role is involved in the modernization program on a full-time basis.

Knowledge, Skills, and Abilities (KSAs)
Thorough understanding of the principles and practices of establishing governance models, data ownership frameworks, and alignment with PMO structures.
Thorough understanding of strategies, methodologies, and tools for large-scale legacy-to-modern system conversions, including mainframe migrations, with the ability to translate program-wide modernization objectives into a data conversion roadmap that supports business continuity.
Techniques for identifying invalid, inconsistent, orphaned, and incomplete data, along with remediation methods and root cause analysis.
Expertise in Oracle, SQL Server, and Erwin Data Modeler, including Erwin Data Modeler implementation and use of the tool for generating documentation and conducting data analysis.
Knowledge of government tax/revenue operations and the specific challenges in modernizing these systems.
Standards for cataloging enterprise data sources and maintaining metadata at database, table, and field levels.
Methods for data reconciliation, validation, and iterative conversion testing within staging environments.
Ability to resolve data ambiguities and conflicts across multiple legacy sources with accuracy and efficiency.
Ability to motivate and guide diverse teams, balancing business and technical perspectives.
Ability to anticipate data-related risks and implement proactive controls to ensure high-quality conversions.
Ability to clearly articulate data strategies, risks, and outcomes to executive stakeholders, SMEs, and vendors.
Adhere to defined project management processes, including risk and issue management, quality management, benefits realization management, and change control.