Data Modeler

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 integrity Create optimized conceptual, logical, and physical data models for the target state architecture Design migration paths that maintain referential integrity and business rule enforcement Identify opportunities for strategic denormalization where justified by performance requirements Migration Strategy & Execution Develop comprehensive migration strategies with minimal or zero downtime requirements Design data transformation logic to migrate from denormalized to normalized structures Create phased migration approaches using patterns such as strangler fig, dual-write, or shadow databases Implement data validation and reconciliation frameworks to ensure migration accuracy Develop rollback strategies and contingency plans for migration phases Coordinate database deployment using CI/CD pipelines and migration tools Performance Optimization & Tuning Benchmark existing system performance to establish baselines Optimize new schema design through indexing strategies, partitioning, and query optimization Conduct load testing and performance validation pre and post-migration Fine-tune database configuration, connection pooling, and caching strategies for AWS Aurora PostgreSQL Ensure normalized design meets or exceeds current performance benchmarks Data 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 architecture Define and enforce data quality standards throughout migration process Establish data lineage and metadata management for new structures Documentation & Knowledge Transfer Create comprehensive documentation including data models, schema specifications, migration procedures, and data dictionaries Develop data flow diagrams, entity-relationship diagrams, and architecture decision records Document rationale for normalization decisions and any strategic denormalization Create runbooks for migration execution and rollback procedures Provide knowledge transfer sessions to technical teams Required Skills & Qualifications Data Modeling & Database Expertise 10+ years of hands-on experience in data modeling and database design 5+ years of experience reverse engineering and refactoring large-scale OLTP databases Expert-level understanding of database normalization theory and practical application (1NF through 5NF, BCNF) Deep expertise in both forward and reverse engineering of data models Proven track record of successful database modernization and schema refactoring projects In-depth knowledge of relational database design principles, patterns, and anti-patterns Technical 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 platforms Strong expertise in data modeling tools ( erwin, SqlDBM, ER/Studio, or similar ) Experience with database migration and version control tools Familiarity with database comparison and schema diff tools Knowledge of database DevOps practices and CI/CD pipeline integration Experience with cloud platforms (AWS, Azure, GCP) and cloud-native database services Relevant certifications (AWS Certified Database Specialty, PostgreSQL certifications) are advantageous