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Wissen Technology is hiring an experienced Data Modeling Architect to design, build, and optimize data models specifically for the Databricks environment. The ideal candidate will have strong hands-on experience in Databricks and proven expertise in creating scalable, efficient, and high-performance data models tailored for Databricks-based architectures. Knowledge of Financial Risk or Operational Risk frameworks used in global banking environments is highly desirable.
Job Responsibility:
Design and implement scalable, efficient, and high-performance data models for Databricks-based environments
Collaborate with cross-functional teams to translate business requirements into robust data models
Optimize data models for performance and scalability in Databricks
Work with Delta Lake, Unity Catalog, and other Databricks components
Ensure data integrity and consistency across models
Support data validation, profiling, and modeling workflows using Python
Provide guidance on best practices for data modeling in cloud-based environments
Incorporate risk-related data structures (Credit Risk, Market Risk, Liquidity Risk, RCSA, Loss Events, KRI, etc.) into models
Requirements:
Proven experience as a Data Modeler with strong understanding of data modeling concepts
Hands-on experience in Databricks and modeling for Databricks-based environments (mandatory)
Strong knowledge of dimensional, relational, and conceptual modeling
Proficiency in Python for data validation and workflow support
Strong SQL skills and familiarity with data warehousing concepts
Experience with Delta Lake, Unity Catalog, or similar Databricks components
Ability to collaborate effectively with cross-functional teams
Working knowledge of Financial Risk, Operational Risk, or regulatory risk data
Strong analytical and problem-solving skills
Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field
Nice to have:
Experience in global banking environments
Familiarity with advanced Databricks features and performance tuning
Exposure to big data technologies and cloud platforms