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