Senior Data Modeler

Globenet Consulting Corp•BELLEVUE, WA

1d•Hybrid

About The Position

We’re looking for a Senior Data Modeler (7+ years) to design, develop, and maintain scalable data models that power enterprise analytics, data warehousing, and modern application development. In this role, you’ll partner closely with engineers, architects, analysts, and business stakeholders to translate complex requirements into high-performing data structures, modeling standards, and documentation that improve usability, governance, and data quality across the organization.

Requirements

7+ years of experience in data modeling, data architecture, or a closely related discipline.
Expert proficiency with modeling tools such as Erwin, ER/Studio, and/or dbt.
Strong experience with relational databases (SQL Server, Oracle, PostgreSQL) and cloud data platforms such as Databricks, Snowflake, BigQuery, Redshift, and Azure Synapse.
Deep knowledge of dimensional modeling approaches (Kimball, Inmon) and Data Vault 2.0.
Advanced SQL skills for schema design, query optimization, and data validation.
Proven ability to work independently, manage competing priorities, and deliver in consulting/contractor-style environments.
Strong communication skills and the ability to explain technical concepts to technical and non-technical audiences.

Nice To Haves

NoSQL experience (MongoDB, Cassandra, DynamoDB).
Lakehouse architecture familiarity (Delta Lake, Apache Iceberg, Apache Hudi).
Exposure to governance/catalog tools (Collibra, Alation, Atlan).
Understanding of data mesh concepts and federated ownership models.
Experience in regulated domains such as finance, healthcare, or retail.

Responsibilities

Design conceptual, logical, and physical data models for relational, dimensional, and NoSQL data stores.
Create and maintain ERDs, data flow diagrams, and modeling documentation aligned to enterprise standards.
Collaborate with engineering and architecture teams to support efficient ingestion, transformation, and reporting pipelines.
Translate business needs into optimized schemas that balance scalability, performance, and maintainability.
Lead data model reviews, enforce standards, and mentor junior team members on best practices.
Develop and maintain data dictionaries, metadata, and lineage documentation to improve discoverability and reuse.
Design star/snowflake schemas for data warehouse and data mart environments in partnership with analytics teams.
Identify and resolve data quality, redundancy, and integrity issues through effective modeling and normalization/denormalization strategies.
Support governance initiatives, including standardization, cataloging, and stewardship alignment.
Participate in Agile delivery, producing modeling artifacts iteratively within sprint cycles.