Senior Enterprise Data Modeler (Cloud Data)

TL;DR

Senior Enterprise Data Modeler (Cloud Data): Leading the design and management of critical data structures for modern cloud data platforms with an accent on scalability, performance, and business alignment. Focus on conceptual, logical, and physical data modeling, optimizing for distributed cloud environments, and integrating structured and semi-structured data.

Location: Dallas, TX or Tulsa, OK

Company

hirify.global Corporation Group is a stable and financially strong organization that provides excellent training and development to support building the long term careers of employees.

What you will do

• Lead the design and implementation of conceptual, logical, and physical data models for cloud-native data platforms.
• Collaborate with data architects, engineers, and business stakeholders to ensure alignment with business requirements.
• Develop and maintain data modeling standards, best practices, and governance processes.
• Optimize data models for performance, scalability, and cost efficiency across distributed cloud environments.
• Provide expertise in schema evolution, partitioning strategies, and metadata management for technologies such as Iceberg, Databricks, and Snowflake.
• Integrate structured and semi-structured data into unified models and mentor junior data modelers.

Requirements

• Bachelor’s Degree in Information Systems, Data Analytics or a related field.
• 10+ years’ experience in data modeling, with at least 5 years’ experience in cloud-native environments.
• Deep expertise in AWS Iceberg, Databricks Delta Lake, and Snowflake or some combination of these.
• Strong understanding of data lakehouse architecture and distributed query engines.
• Proficiency in SQL, Python, and data modeling tools (e.g., ER/Studio, ERwin, dbt).
• Experience with data governance, metadata management, and data cataloging tools.
• Well-developed oral and written English communication skills.

Nice to have

• Experience within the financial services industry, including regulatory requirements and financial data domains.
• Experience with enterprise data architecture frameworks (e.g., DAMA-DMBOK, TOGAF).
• Familiarity with real-time data processing and streaming architectures.

Culture & Benefits

• Team thrives on collaboration, continuous learning, and innovation.
• Leverage cutting-edge technologies and share expertise to solve complex problems.
• Encourages creativity and adaptability, fostering a dynamic and tech-forward work environment.
• Focus on creating a positive and supportive atmosphere.
• Provides excellent training and development for long-term careers.
• Discretionary bonus type.