Senior Data Migration & Validation Analyst

MWCIA - Minnesota Workers Compensation Insurers Association, Inc.•Minneapolis, MN

About The Position

The Senior Data Migration & Validation Analyst is a hands-on individual contributor responsible for ensuring the integrity, reliability, and readiness of business-critical data as MWCIA transitions from legacy Spectrum, MPS, and MUSR systems into Voyageur. The role covers data validation, reconciliation, data-quality analysis, technical troubleshooting, and migration-readiness support throughout the project lifecycle. The analyst independently examines complex data structures, develops advanced SQL queries, validates source-to-target mappings, investigates discrepancies, and creates repeatable reconciliation processes. The role works with business owners, technical teams, and project partners to turn findings into recommendations that support informed decisions and successful implementation. It directly contributes to reducing migration risk, maintaining operational continuity, and establishing a reliable data foundation for MWCIA's future. The position is primarily technical rather than project-management or coordination focused. Responsibilities include executing end-to-end migration validation and reconciliation; profiling data and validating mappings, transformations, and business rules; reconciling insurance information such as premium, loss, exposure, and payroll; and supporting mock migrations, production cutover, production acceptance, and post-implementation issue resolution. The analyst also evaluates database models and structures, tests integrity and data quality, investigates defects, supports corrective actions and regression testing, maintains technical and audit documentation, and contributes to legacy-system decommissioning validation.

Requirements

Bachelor's degree in Computer Science, Information Technology, Data Science, or a related discipline, or an equivalent combination of education and relevant professional experience.
Demonstrated hands-on experience with complex data migration and validation.
Advanced SQL development and database analysis experience.
Experience working with relational databases, data modeling, data reconciliation, and data-quality processes.
Demonstrated ability to investigate and resolve complex technical data issues independently.
Ability to develop, troubleshoot, and optimize complex SQL queries.
Ability to interpret Oracle database structures and relational data models.
Knowledge of database normalization principles and sound data-design practices.
Ability to analyze source-to-target mappings, transformation logic, and business rules.
Ability to develop and implement data-quality checks, automated comparisons, and exception reporting.
Ability to evaluate whether migrated data is accurate, traceable, and suitable for operational and analytical use.
Understanding of Azure SQL troubleshooting and diagnostic practices.
Understanding of software development lifecycle principles and tools such as Git and Azure DevOps.
Understanding of CI/CD practices and Agile or Scrum delivery methodologies.
Strong analytical reasoning, attention to detail, accountability, and technical problem-solving ability.
Ability to communicate complex technical findings clearly and translate technical results into understandable business information.
Ability to collaborate across technical teams, business functions, and external partners, work independently, and adapt to changing priorities.

Nice To Haves

Experience working with complex, high-volume, business-critical datasets.
Experience supporting enterprise technology modernization, system conversions, or legacy-system retirement.
Experience within insurance, workers' compensation, financial services, or another data-intensive industry.
Experience developing automated validation and reconciliation solutions.

Responsibilities

Independently execute end-to-end validation and reconciliation of data migrating from legacy systems into Voyageur.
Profile source data to identify inconsistencies, gaps, anomalies, and potential migration risks.
Validate source-to-target data mappings, transformations, and business rules.
Develop, execute, troubleshoot, and optimize advanced SQL queries for data analysis, validation, and reconciliation.
Perform record-count reconciliation, automated field-level comparisons, and exception reporting.
Reconcile critical insurance data, including premium, loss, exposure, and payroll information.
Validate CST-to-UST transformations and related requirements.
Develop repeatable validation procedures and automated reconciliation solutions.
Support mock migrations, identify defects, and verify corrective actions.
Create, interpret, and evaluate conceptual, logical, and physical entity relationship models.
Compare source and target database structures to identify mapping gaps, structural differences, and potential data-integrity risks.
Identify modeling issues involving missing keys, ambiguous relationships, circular dependencies, and incorrectly assigned attributes.
Test referential integrity, duplicate keys, orphaned foreign keys, relationship cardinality, and missing required values.
Evaluate schema security models and applicable data-access requirements.
Investigate data-quality issues, identify root causes, and develop or recommend corrective solutions.
Collaborate with technical and business teams to resolve defects and perform regression testing.
Identify opportunities to improve data quality, validation efficiency, and long-term reliability.
Execute validation activities supporting migration readiness and production acceptance.
Evaluate reconciliation results, identify outstanding risks, and provide evidence-based recommendations for go/no-go decisions.
Support production cutover validation, reconciliation, and signoff coordination.
Monitor data quality following implementation and assist with post-production issue resolution.
Support legacy-system decommissioning by validating data completeness, accuracy, and traceability.
Maintain requirements, technical documentation, validation evidence, testing results, operational runbooks, and audit records.
Partner with Data Services, IT, Quality Assurance, business owners, and external vendors to support project outcomes.
Design, develop, maintain, and optimize solutions within Microsoft SQL Server environments.
Apply Azure Data Factory or comparable data-integration technologies to support data movement, transformation, and automation.
Communicate technical findings, risks, dependencies, recommendations, and progress to technical and nontechnical stakeholders.
Work independently while maintaining accountability to shared team and organizational goals.