Data Modeler

• Responsible for designing and implementing conceptual, logical, and physical data models for enterprise data platforms, data warehouses, and data lakes.
• Works closely with Data Engineering and Data Analytics teams to develop scalable and reusable data structures across business units.
• Supports enterprise data architecture initiatives, dimensional modeling, governance, and metadata management practices.
• Provides expertise in modern data technologies including Databricks, dbt, Dagster, and Snowflake., * Design and maintain conceptual, logical, and physical data models.
• Develop dimensional models and conformed dimensions for enterprise reporting and analytics.
• Collaborate with Data Engineering and Analytics teams to support scalable data solutions.
• Create and maintain documentation for data models and architecture standards.
• Query and profile data sources to ensure data quality and consistency.
• Support enterprise data architecture and governance initiatives.
• Provide guidance on database technologies, trends, and best practices.
• Work with stakeholders to translate business requirements into data structures.
• Support metadata management and governance processes.
• Participate in design reviews and data architecture discussions.

• 7 years of experience with Databricks.
• 7 years of experience with dbt.
• 7 years of experience with Dagster.
• 7 years of experience with Elementary.
• 7 years of experience in Data Modeling.
• Strong conceptual, logical, and physical data modeling expertise.
• Experience with dimensional modeling and conformed dimensions across business units.
• Experience using data modeling tools such as PowerDesigner, Oracle Designer, or Erwin.
• Ability to write SQL queries and perform data analysis.
• Strong understanding of database technologies and data architecture principles.
• Excellent written and verbal communication skills.
• Ability to explain data structures to non-technical audiences.
• Strong interpersonal, negotiation, and influencing skills.
• Ability to work independently and deliver results.

Experience:

• Experience in data engineering and data modeling for data warehouses and data lakes.
• Experience working with Data Engineering and Data Analytics teams.
• Experience querying and profiling data sources.
• Experience using data modeling tools and methodologies.
• Experience with enterprise-level data architecture initiatives., * Experience in banking or financial services domain.
• Experience with Snowflake.
• Experience with data governance and metadata management tools.
• Experience with enterprise data warehouse and data lake environments.

Skills:

• Data modeling and architecture.
• Databricks, dbt, Dagster, and Elementary.
• SQL and data querying.
• Dimensional modeling and data warehousing.
• Database technologies and optimization.
• Data governance and metadata management.
• Documentation and stakeholder communication.
• Analytical and problem-solving skills.