Job Description:
Role Summary: We are seeking a meticulous and experienced Data Modeler (Mid to Senior Level) with 4-7 years of relevant experience to join our public sector agency. You will be responsible for designing, developing, and maintaining the enterprise-wide conceptual, logical, and physical data models that form the foundation of our data architecture and governance framework within the AWS cloud environment. Your expertise in data modeling tools (like ERwin, ER/Studio, PowerDesigner) and database technologies will ensure our data structures are consistent, scalable, high-quality, and compliant with public sector standards, effectively supporting analytics, reporting, ML initiatives, and agency mandates.
Key Responsibilities:
- Data Model Design & Maintenance:
Develop, document, and maintain canonical, conceptual, logical, and physical data models using industry best practices and agency-specific requirements.
Ensure models accurately represent business processes and data relationships, aligning with both current needs and future strategic direction.
Iteratively evolve and extend data models to incorporate new data sources, features, and diverse use cases (analytics, operational reporting, ML/AI). - Governance & Standards Enforcement:
Define, document, and actively enforce enterprise data modeling standards, naming conventions, data types, and best practices within the agency.
Partner closely with the Data Governance and Data Catalog teams to ensure data models are accurately reflected in the metadata repository (e.g., using Collibra, Atlan, AWS Glue Data Catalog) and align with overall governance policies.
Ensure models adhere to relevant public sector data security and compliance mandates. - Collaboration & Review:
Work collaboratively with Data Architects, Data Engineers, Business Analysts, and application development teams to translate functional and non-functional requirements into robust, optimized data models.
Lead and participate in data model review sessions, conduct impact assessments for proposed changes, and ensure backward/forward compatibility of model versions. - Documentation & Training:
Produce clear, comprehensive data model documentation, including entity-relationship diagrams (ERDs), data dictionaries, data flow diagrams, and model release notes.
Provide training, guidance, and support to technical teams and business stakeholders on interpreting, utilizing, and extending the established data models. - Quality & Performance:
Validate data models against data quality rules, business requirements, and data lineage information to ensure accuracy and integrity.
Optimize data models (physical) for query performance, considering indexing strategies, partitioning, and integration patterns with ETL/ELT processes within the AWS environment.
Required Qualifications:
- Experience: 4-7 years of hands-on professional experience focused on enterprise data modeling, data architecture, and database design.
- Education: Diploma or Bachelor’s Degree in Computer Science, Information Systems, Information Management, or a related field.
- Modeling Tool Expertise: Expert proficiency and significant experience using one or more leading data modeling tools (e.g., ERwin Data Modeler, ER/Studio Data Architect, SAP PowerDesigner, or open-source equivalents like Archi).
- Database Knowledge: Strong understanding of relational database principles (e.g., for PostgreSQL, Oracle) and familiarity with NoSQL database concepts (e.g., MongoDB).
- SQL/DDL Proficiency: Strong proficiency in SQL, including Data Definition Language (DDL) for creating and modifying database structures.
- Governance Acumen: Solid understanding of data governance principles, metadata management concepts, and the role of data modeling within a governance framework.
- Communication Skills: Proven ability to clearly articulate complex data models, technical concepts, and design rationale to diverse audiences (both technical and non-technical).
Preferred (Nice-to-Have) Qualifications:
- Cloud Exposure: Experience working within cloud-based data environments, particularly AWS (e.g., designing models for data lakes on S3, interacting with AWS Glue Data Catalog, AWS Lake Formation).
- Metadata Platform Familiarity: Hands-on experience or familiarity with metadata management / data catalog platforms (e.g., Collibra, Alation, Atlan).
- Public Sector Experience: Prior experience working within or delivering data modeling solutions for the Singapore Public Sector.
- Modeling Paradigms: Experience with various modeling techniques such as Dimensional Modeling (Kimball/Inmon), Data Vault, or NoSQL modeling patterns.
- Standards Knowledge: Familiarity with relevant government data standards or architectural frameworks.
Technical Environment / Tools:
- Data Modeling Tools (e.g., ERwin, ER/Studio, PowerDesigner, Archi)
- Databases (e.g., PostgreSQL, Oracle, MongoDB)
- SQL, DDL
- Cloud Platform (AWS: Glue Data Catalog, S3, Lake Formation - exposure preferred)
- Metadata Platforms (e.g., Collibra, Atlan - familiarity preferred)