Database Full Stack Developer

• Analyze legacy database schemas, stored procedures, triggers, and embedded business logic; reconstruct lineage and rules using AI-assisted analysis.

• Design the target-state relational model, including normalization, indexing, partitioning, and referential integrity strategy.

• Build and tune data access layers spanning persistence code and database objects, working across application and data tiers.

• Develop and execute data migration, reconciliation, and parallel-run validation, including AI-generated test data and comparison harnesses.

• Implement data security controls: encryption, masking, row-level access, and audit logging appropriate to sensitive case data.

• Optimize query and transaction performance against production workload profiles; remediate regressions introduced by migration.

Document converted business rules so they are traceable from legacy source to target implementation

Minimum Education: Bachelor’s degree in Computer Science, Information Technology, or a related field. Two (2) years of specialized experience may substitute for one (1) year of the academic requirement.

Minimum Experience: Five (5) to eight (8) years of experience spanning database engineering and application development, including at least two (2) years of experience in data migration or legacy conversion, along with demonstrated use of AI-assisted tools for schema or code analysis.

Certifications: One required certification and one certification obtainable after hire. Preferred certifications include Microsoft Certified: Azure Database Administrator Associate, Oracle Database Administrator Certified Professional, AWS Certified Database - Specialty, Microsoft Certified: Azure AI Engineer Associate, or SnowPro Core.

Required Skills: Advanced SQL and query tuning, relational data modeling, stored procedure and trigger analysis, data migration and reconciliation, Java or equivalent persistence frameworks such as JPA and Hibernate, AI-assisted schema and code analysis, and database security controls.

Preferred Skills: Familiarity with Delphi or legacy 4GL data access patterns, Oracle-to-PostgreSQL or SQL Server conversion, retrieval-augmented generation (RAG) over legacy database documentation, experience with high-volume transactional systems, and federal-sector experience.

Technical Environment: PostgreSQL, Microsoft SQL Server, Oracle Database, Java with Spring Data, JPA and Hibernate, Liquibase or Flyway for schema change management, SSIS, AWS DMS or equivalent migration tools, AI-assisted code and schema analysis tools, dbt for transformation testing, Transparent Data Encryption, dynamic data masking, query plan analysis, performance tuning tools, Git, and CI/CD pipelines.

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