Senior Data Migration Lead

Senior Data Migration / Data Purging Lead – R&D Applications Location: 100% Remote (Must work EST hours) Engagement Type: Long-Term Contract Employment Model: W2 Only (Must be a US Citizen or Green Card Holder; no C2C or sponsorship) Experience Level: 10–15 Years Industry/Context: Large-scale Manufacturing engagement supporting a Big 4 Consulting firm Role Overview We are looking for a Senior Data Migration / Data Purging Lead to own the technical data workstream for a critical R&D and Engineering application separation and migration program. Supporting a Big 4 consulting client within the manufacturing domain, you will lead the definition and execution of data profiling, target extraction, ETL script development, complex relational data purging, reconciliation, and cutover validation. Key Responsibilities Lead data discovery and requirements assessment alongside application owners, R&D/Engineering SMEs, database administrators, and functional stakeholders. Inventory and classify source data across relational databases, document repositories, file stores, and interfaces to define migration, retention, archival, and purging scopes. Translate business and legal data policies into technical purge rules, building precise selection criteria, filters, exclusions, and dependency rules. Analyze complex object dependencies, including multi-level parent/child relationships and referential integrity, ensuring zero unintended data loss during purge/migration runs. Perform comprehensive data profiling and quality assessments, establishing automated pre- and post-purge validation criteria and discrepancy thresholds. Design the end-to-end data migration pipeline, spanning extraction, data cleansing, transformation, target loading, exception routing, and audit trails. Develop and execute high-performance SQL scripts, stored procedures, ETL/ELT workflows, APIs, and custom migration/purging utilities. Drive non-production mock runs, code reviews, integration testing, SIT/UAT support, production cutovers, and hypercare triage. Implement automated reconciliation frameworks using control totals, row counts, hash checks, and variance reports to prove data accuracy to program leadership and audit teams. Required Qualifications 10–15 years of focused experience in data migration, data engineering, database development, ETL design, or large-scale enterprise application data conversions. Direct experience leading data workstreams for major carve-outs, divestitures, M&A separations, TSA exits, or platform modernizations. Advanced hands-on expertise in SQL and relational database platforms, including Microsoft SQL Server, Oracle, PostgreSQL, or enterprise equivalents. Demonstrated track record writing and executing complex data migration and data-purging routines against large-volume production databases. Deep proficiency in ETL/ELT architectures, data mapping frameworks, batch pipelines, and integration patterns. Expertise in relational data modeling, referential integrity enforcement, and resolving nested parent/child data dependencies. Proven capability handling both structured data and unstructured content (such as engineering CAD files, specifications, PDFs, and flat repositories). Strong experience establishing data reconciliation frameworks, control checks, source-to-target balancing, and audit controls. Hands-on involvement in dry runs, mock cutovers, production cutovers, and post-cutover operational stabilization. Strong root-cause analysis and troubleshooting acumen, with a methodical approach to resolving data corruption, constraint violations, and performance bottlenecks. Ability to interface directly with client business and legal teams to translate complex compliance and retention guidelines into executable technical code.