The Principal Data Modeler / Architect will lead a critical database modernization initiative to reverse engineer, redesign, and normalize our existing OLTP data architecture. This role requires a seasoned data professional who can analyze complex legacy systems, identify architectural debt, and execute a comprehensive schema refactoring strategy while ensuring zero business disruption. The ideal candidate combines deep expertise in data modeling, normalization principles, and large-scale database migration with strong collaboration skills to coordinate cross-functional teams through this transformation.
Experience in the EdTech domain is a plus.
Primary Objective
Reverse engineer our existing large-scale OLTP database, analyze current denormalized structures, and redesign the data model following normalization best practices while optimizing for performance, maintainability, and scalability in a modern SaaS environment.
Key Responsibilities
Database Analysis & Reverse Engineering
- Reverse engineer existing OLTP databases to create comprehensive conceptual, logical, and physical data models
- Analyze current schema design to identify denormalization patterns, data redundancies, integrity issues, and architectural debt
- Profile existing data quality, identify anomalies, inconsistencies, and constraint violations
- Document current state architecture, data flows, and integration points
Schema Redesign & Normalization
Redesign database schema by applying normalization principles (1NF through BCNF) to eliminate redundancy and improve data integrityCreate optimized conceptual, logical, and physical data models for the target state architectureDesign migration paths that maintain referential integrity and business rule enforcementIdentify opportunities for strategic denormalization where justified by performance requirementsMigration Strategy & Execution
Develop comprehensive migration strategies with minimal or zero downtime requirementsDesign data transformation logic to migrate from denormalized to normalized structuresCreate phased migration approaches using patterns such as strangler fig, dual-write, or shadow databasesImplement data validation and reconciliation frameworks to ensure migration accuracyDevelop rollback strategies and contingency plans for migration phasesCoordinate database deployment using CI / CD pipelines and migration toolsPerformance Optimization & Tuning
Benchmark existing system performance to establish baselinesOptimize new schema design through indexing strategies, partitioning, and query optimizationConduct load testing and performance validation pre and post-migrationFine-tune database configuration, connection pooling, and caching strategies for AWS Aurora PostgreSQLEnsure normalized design meets or exceeds current performance benchmarksData Governance, Security & Compliance
Ensure redesigned data model maintains compliance with relevant standards (GDPR, HIPAA, FERPA for EdTech)Implement data governance policies, access controls, and security measures in new architectureDefine and enforce data quality standards throughout migration processEstablish data lineage and metadata management for new structuresDocumentation & Knowledge Transfer
Create comprehensive documentation including data models, schema specifications, migration procedures, and data dictionariesDevelop data flow diagrams, entity-relationship diagrams, and architecture decision recordsDocument rationale for normalization decisions and any strategic denormalizationCreate runbooks for migration execution and rollback proceduresProvide knowledge transfer sessions to technical teamsRequired Skills & Qualifications
Data Modeling & Database Expertise
10+ years of hands-on experience in data modeling and database design5+ years of experience reverse engineering and refactoring large-scale OLTP databasesExpert-level understanding of database normalization theory and practical application (1NF through 5NF, BCNF)Deep expertise in both forward and reverse engineering of data modelsProven track record of successful database modernization and schema refactoring projectsIn-depth knowledge of relational database design principles, patterns, and anti-patternsTechnical Proficiency
Expert-level SQL skills and extensive experience with PostgreSQL (required)Proficiency with additional RDBMS platforms (SQL Server, Oracle, MySQL)Hands-on experience with AWS Aurora PostgreSQL or similar cloud-based database platformsStrong expertise in data modeling tools ( erwin, SqlDBM, ER / Studio, or similar )Experience with database migration and version control toolsFamiliarity with database comparison and schema diff toolsKnowledge of database DevOps practices and CI / CD pipeline integrationExperience with cloud platforms (AWS, Azure, GCP) and cloud-native database servicesRelevant certifications (AWS Certified Database Specialty, PostgreSQL certifications) are advantageous