Data Modeler

Job Summary

We are seeking a Data Modeler with strong knowledge and experience in Data Warehousing and related disciplines. The primary purpose of this role is to design and manage the data architecture necessary to support the Enterprise Analytics Ecosystem. The Data Modeler will ensure efficient data processes and collaboration across various teams, helping to enhance analytics and reporting capabilities.

Responsibilities

• Design and manage the data architecture for the Enterprise Analytics Ecosystem.
• Develop conceptual, logical, and physical data models that are scalable and efficient.
• Maintain and update data dictionaries for easy reference and clarity.
• Collaborate effectively with stakeholders, including Business Analysts and Data Engineers, to align data modeling to business requirements.
• Conduct data discovery discussions with business stakeholders during Joint Application Design (JAD) sessions.
• Explain data models to the ETL team and work closely with them to create data process pipelines for ingestion and transformation.
• Support various analyst communities by providing insights and assessments of data assets.
• Ensure that database designs effectively support Business Intelligence (BI) and end-user requirements.
• Document and establish best practices in data modeling standards.
• Ensure compliance with data security standards and privacy regulations.

Qualifications

• Strong experience in Data Modeling as a core skill.
• Proficient in SQL and ETL processes.
• Hands-on experience with Cloud platforms (AWS or Azure).
• Knowledge of Modern Data Architecture (including Gold-Silver-Bronze layers).
• Preferably experience in Data Warehousing, particularly with Dimensional Modeling, Star and Snowflake Schema.
• Familiarity with modeling tools such as ERWIN or other industry-standard tools.
• Strong understanding of database design principles and effective data modeling techniques.
• Ability to maintain current knowledge of industry trends and standards.

Preferred Skills

• Experience with large relational databases like Synapse, GCP, or Redshift.
• Familiarity with data security standards and regulations.

Experience

• Relevant experience is preferred but not explicitly stated; a strong background in data modeling and warehousing is critical.