Data Modeller

Responsibilities

• Design and maintain conceptual, logical, and physical data models tailored for modern cloud data warehousing (e.g., BigQuery).
• Implement best practices for data modeling techniques, including Dimensional Modeling (Kimball), Data Vault 2.0, and normalized (3NF) structures.
• Collaborate with business stakeholders and data architects to analyze business requirements and translate them into scalable data layouts.
• Define and enforce data governance, data lineage, and metadata management standards across data pipelines.
• Optimize data models for query performance, storage efficiency, and cost-effectiveness within Google Cloud Platform (GCP).
• Create and maintain comprehensive data documentation, including data dictionaries, entity-relationship diagrams (ERDs), and mapping documents.
• Partner with Data Engineers to ensure underlying ETL/ELT processes align perfectly with the designed data models.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, or a related technical field.
• 4+ years of experience in data modeling, data architecture, or data engineering roles.
• Strong expertise in relational and non-relational database design, with proven experience building large-scale enterprise data warehouses.
• Hands-on experience with Google Cloud Platform (GCP) data services, particularly BigQuery, Cloud Spanner, or Cloud SQL.
• Proficiency in data modeling tools such as Erwin, ER/Studio, or dbt (data build tool).
• Advanced SQL skills for data analysis, profiling, and validation.
• Strong understanding of data governance, data privacy (GDPR/CCPA compliance), and master data management (MDM) concepts.
• Excellent communication skills with the ability to explain complex technical data concepts to non-technical stakeholders.
• Google Cloud Professional Data Engineer certification is a strong plus.
• AI Transparency & Disclosure
• As an AI transformation partner, 66degrees leverages intelligent solutions to enhance our recruitment experience. We utilize AI tools-including LinkedIn Recruiter's Hiring Assistant and interview transcription technologies-to assist with sourcing, role analysis, and capturing interview highlights.
• These tools augment our process, but we "Commit to Our Craft" by ensuring all final hiring de

Benefits

Additional Information

Overview of 66degrees 66degrees is an end-to-end AI transformation partner that guides enterprises from complex business challenges to clear, quantifiable outcomes. Our company is the culmination of several successful firms, each a leader in its own right in cloud, artificial intelligence, and data. This convergence of talent and expertise is how we help businesses reach their own "inflection point," where chaotic data becomes a strategic asset, complexity becomes clarity, and AI becomes an engine for growth. Our ultimate vision is to be the catalyst for a future where every business operates as an intelligent enterprise, with autonomous systems unlocking human potential. At 66degrees, we believe in thriving through challenges and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way. Overview of 66degrees 66degrees is a leading Google Cloud Premier Partner. We believe that engineering takes heart. Focusing exclusively on Google Cloud, we help our clients achieve the most innovative and disruptive transformations in their industries. 66degrees is dedicated to providing our employees with a challenging and exciting work environment without forgetting to have some fun along the way. Let's get you here. Overview of Role As a Data Modeler at 66degrees, you will be responsible for designing, implementing, and optimizing robust data models that power our clients' modern data platforms on Google Cloud. You will bridge the gap between complex business requirements and technical data architecture, ensuring scalability, high performance, and data integrity. In this role, you will work closely with Data Engineers, Architects, and Analytics teams to transform raw data structures into highly optimized enterprise data assets using cutting-edge cloud technologies.

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