Position: DATA ENGINEER (DATA MODELER)
Experience: 10+ YEARS
Location: COLUMBUS, OH (REMOTE)
Employment Type: CONTRACT (W2/1099 ONLY)
Visa Type: USC
Summary:
Role Overview
We are seeking a highly experienced Data Modeler to design and implement enterprise-grade data solutions. This role requires deep expertise in data modeling principles, data architecture frameworks, and modern cloud-based platforms. The candidate will play a critical role in shaping our data ecosystem, ensuring scalability, performance, and alignment with business needs.
Key Responsibilities
Data Modeling:
• Design conceptual, logical, and physical data models for structured and semi-structured data.
• Define entity relationships, normalization/denormalization strategies, and dimensional modeling for analytics.
• Develop star and snowflake schemas for data warehouses and analytical workloads.
• Ensure data integrity, consistency, and compliance with governance standards.
Data Architecture:
• Architect end-to-end data solutions leveraging modern frameworks and best practices.
• Implement Medallion architecture (Bronze, Silver, Gold layers) for scalable data pipelines.
• Optimize data storage and retrieval strategies for performance and cost efficiency.
• Collaborate with engineering teams to design data ingestion, transformation, and integration workflows.
Technology Stack:
• Hands-on experience with Google BigQuery for large-scale analytics.
• Expertise in Databricks for data engineering and advanced analytics.
• Familiarity with cloud-native architectures, distributed systems, and data lakehouse concepts.
Required Qualifications
• 10+ years of experience in data modeling and data architecture.
• Proven track record in designing enterprise data warehouses and analytical platforms.
• Strong understanding of Medallion architecture and modern data lakehouse design.
• Proficiency in SQL, data modeling tools (e.g., ERwin, PowerDesigner), and ETL/ELT frameworks.
• Hands-on experience with Google BigQuery and Databricks.
Skills: Preferred Skills
• Knowledge of data governance, metadata management, and master data management.
• Experience with performance tuning and query optimization in large-scale environments.
• Familiarity with data security and compliance standards.