Decompose complex data and business problems into specifications precise enough for AI agents to implement directly and concretely.
Design and maintain a repeatable migration pipeline that consolidates legacy mirrored Oracle schemas into a modern, single-schema PostgreSQL environment.
Implement rigorous automated reconciliation machinery (checksums, financial control totals, and row counts) to provide government acceptance evidence.
Conduct "legacy archaeology" by interrogating hundreds of thousands of lines of PL/SQL packages and triggers to extract and document load-bearing business rules.
Develop transactional schemas using Prisma and design Change Data Capture (CDC) workflows into dedicated analytics stores.
Build complete vertical slices of capability, including React-based admin UIs for data quality reports and Node.js API endpoints.
Set the technical bar for data integrity, utilizing golden-master behavioral checks to prove migrated cases still price and process identically to legacy systems.
Maintain a rigorous human-review process for all agent-generated code to ensure compliance with federal financial standards.
Requirements
Experience with heterogeneous migrations, specifically moving from Oracle to PostgreSQL.
Familiarity with data modeling for analytics and replacing legacy reporting estates like Cognos.
Background in financial data systems or environments subject to strict federal audit standards.
Experience with AWS GovCloud, CDK, and containerized deployments (EKS/ECS).
Experience with data-quality tooling and synthetic data generation.
Prior work in a regulated government environment (FedRAMP, RMF, or IL-specific programs).
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