JD Summary
We are seeking an experienced Data Modeler with deep expertise in enterprise system migration and modernization programs, preferably within the financial domain. The ideal candidate will play a pivotal role in decommissioning legacy systems and designing future-ready data platforms using PostgreSQL. This role requires strong hands-on experience in large-scale data modeling, migration, and modernization initiatives involving complex, high-volume datasets.
Required Qualifications
- 7+ years of hands-on experience in data modeling and data migration for complex enterprise systems, handling high-volume datasets.
- Proven experience migrating complex data from legacy systems such as SQL/MP and Enscribe to PostgreSQL.
- Deep expertise in PostgreSQL performance and migration capabilities, including:
- Large-scale COPY operations
- Foreign Data Wrappers (FDW)
- Table partitioning strategies
- Parallel query processing
Preferred Skills (Good to Have)
- Experience with data modeling tools such as PlantUML, Draw.io, or similar.
- Familiarity with data reconciliation frameworks and validation approaches.
- Prior involvement in reporting migrations or reference data modernization initiatives.
Key Responsibilities
- Lead conceptual, logical, and physical data modeling for enterprise-wide financial system modernization and core platform replacement programs.
- Perform data re-modelling to support transactional, analytical, and regulatory workloads.
- Conduct legacy data discovery and profiling, and create detailed Source-to-Target Mappings (STTM) for migrations involving hundreds of tables.
- Define and execute end-to-end data migration strategies from legacy platforms to PostgreSQL.
- Collaborate closely with solution architects, data engineers, and business stakeholders to ensure data models align with business and technology requirements.
- Produce high-quality deliverables, including:
1.ER diagrams
2.Data dictionaries
3.Data mappings
4.Migration runbooks
5.Reconciliation and validation reports
- Enforce data governance, data quality, masking, and compliance standards throughout the migration lifecycle.
