Senior Enterprise Data Modeler
Role details
Job location
Tech stack
Job description
The Senior Enterprise Data Modeler is responsible for drafting and managing critical data structures for current and future needs. This position will lead enterprise data modeling initiatives across modern cloud data platforms such as AWS Iceberg, Databricks, and Snowflake. The Senior Enterprise Data Modeler will be instrumental in designing scalable, performant, and business-aligned data models that support advanced analytics, data science, and enterprise reporting needs. Team Culture
Our team thrives on collaboration, continuous learning, and innovation. We work closely together, leveraging cutting-edge technologies and sharing our expertise to solve complex problems efficiently. By encouraging creativity and adaptability, we experiment with new tools and methodologies, fostering a dynamic and tech-forward work environment. Additionally, we focus on creating a positive and supportive atmosphere, ensuring everyone feels valued and motivated to excel. How You'll Spend Your Time
- You will lead the design and implementation of conceptual, logical, and physical data models for cloud-native data platforms.
- You will collaborate with data architects, engineers, and business stakeholders to ensure alignment with business requirements and enterprise data strategy.
- You will develop and maintain data modeling standards, best practices, and governance processes.
- You will optimize data models for performance, scalability, and cost efficiency across distributed cloud environments.
- You will provide expertise in schema evolution, partitioning strategies, and metadata management for technologies such as Iceberg, Databricks, and Snowflake.
- You will integrate structured and semi-structured data into unified models while mentoring junior data modelers and contributing to enterprise architecture efforts.
Requirements
The required level of knowledge is normally acquired through completion of a Bachelor's Degree in Information Systems, Data Analytics or a related field and 10+ years' experience in data modeling, with at least 5 years' experience in cloud-native environments. Experience within the financial services industry is preferred.
- Deep expertise in AWS Iceberg, Databricks Delta Lake, and Snowflake or some combination of these
- Strong understanding of data lakehouse architecture, columnar storage formats, 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
- Proven ability to work across business and technical teams to translate requirements into scalable data models
- Experience with enterprise data architecture frameworks (e.g., DAMA-DMBOK, TOGAF)
- Experience in the financial services industry, with a strong understanding of regulatory requirements, data privacy, and financial data domains (e.g., risk, compliance, trading, payments)
- Familiarity with real-time data processing and streaming architectures
- Experience in Snowflake, AWS, or Databricks are a plus
- Well-developed oral and written communication skills to effectively represent self and BOKF, as well as ability to present complex information and issues in a clear and concise manner
