Data Modeler; Hybrid

Key Responsibilities

• Design and develop conceptual, logical, and physical data models for relational, dimensional, and No
  
  SQL data stores.
• Build and maintain entity‑relationship diagrams (ERDs) and data flow documentation aligned with enterprise data standards.
• Partner with data platform engineers and architects to ensure data models support efficient ingestion, transformation, and reporting pipelines.
• Translate business requirements and use cases into optimized database schemas, ensuring scalability and performance.
• Conduct data model reviews, enforce modeling standards and best practices, and provide technical guidance to junior team members.
• Develop and maintain comprehensive data dictionaries, metadata documentation, and lineage documentation.
• Collaborate with reporting and analytics teams to design star/snowflake schemas for data warehouse and data mart environments.
• Identify and resolve data quality, redundancy, and integrity issues through sound modeling practice.
• Support data governance initiatives including data standardization and data cataloging efforts.
• Participate in an Agile delivery model, delivering modeling artifacts in iterative sprints.

• 7+ years of experience in data modeling, data architecture, or a closely related discipline.
• Expert proficiency in data modeling tools such as Erwin, ER/Studio, and dbt.
• Deep experience with relational databases (SQL Server, Oracle, PostgreSQL) and cloud data platforms (Databricks, Snowflake, Big Query, Redshift, Azure Synapse).
• Strong command of dimensional modeling techniques (Kimball, Inmon, Data Vault 2.0).
• Proficiency in SQL for schema design, query optimization, and data validation.
• Demonstrated ability to work independently, manage competing priorities, and deliver in a contractor/consulting capacity.
• Strong communication skills with the ability to present complex data concepts to both technical and non‑technical audiences.