Senior Data Modeler
Job Title: Senior Data Modeler
Department: Data & Analytics / Enterprise Architecture
Reports To: Director of Data Management
Position Overview:
The Senior Data Modeler designs, develops, and implements enterprise data models to support business intelligence, analytics, and operational systems. This role translates complex business requirements into conceptual, logical, and physical data models, ensuring data integrity, scalability, and alignment with the organization's strategic data vision. The Senior Data Modeler acts as a subject matter expert and mentor to junior team members.
Key Responsibilities:
- Lead the design and development of scalable and sustainable conceptual, logical, and physical data models for enterprise data warehouses, data marts, and operational databases.
- Collaborate with business stakeholders, data analysts, and architects to understand data requirements and define data standards and principles.
- Perform source system analysis and data profiling to inform model design and ensure data quality.
- Implement data models in SQL and NoSQL environments (e.g., SQL Server, Oracle, Snowflake, PostgreSQL).
- Define and govern data naming standards, metadata management practices, and data modeling methodologies (e.g., Kimball, Inmon, Data Vault 2.0).
- Create and maintain comprehensive data model documentation, including entity-relationship diagrams (ERDs), data dictionaries, and lineage.
- Optimize data models for performance, storage, and efficient data retrieval.
- Evaluate and recommend data modeling tools and technologies.
- Mentor junior data modelers and promote data modeling best practices across the organization.
- Partner with ETL developers and DBAs to ensure accurate and efficient model implementation.
Qualifications & Skills:
- Required: Bachelor’s degree in Computer Science, Information Systems, or a related field.
- Preferred: Master’s degree or relevant certifications (e.g., CDMP).
- Required: 7+ years of hands-on data modeling experience in complex enterprise environments.
- Expertise in relational and dimensional modeling techniques.
- Deep proficiency in SQL and experience with modern cloud data platforms (e.g., AWS Redshift, Azure Synapse, Google BigQuery, Snowflake).
- Hands-on experience with data modeling tools (e.g., ER/Studio, ERwin, SAP PowerDesigner, or Lucidchart).
- Strong understanding of master data management (MDM), metadata management, and data governance concepts.
- Excellent communication and stakeholder management skills, with the ability to explain technical concepts to non-technical audiences.
- Proven leadership and mentoring capabilities.
