(Hybrid) Data Modeler at Major Japanese Bank

DURATION : 2025 / 12 / 08-2026 / 12 / 07 SUMMARY : Our client, a major Japanese bank is looking for Data Modeler, responsible for designing and deploying robust, scalable data models and pipelines to support analytics and data product development in the retail banking sector. The successful candidate will have a strong command of financial data and analytics, extensive experience with Google Cloud Platform (Google Cloud Platform) and BigQuery, and advanced expertise in relational and dimensional modeling techniques, coupled with the capability to manage and transform large-scale structured and unstructured datasets. PRINCIPAL DUTIES AND RESPONSIBILITIES : Design and implement relational and dimensional data models for enterprise data warehouses. Develop conceptual, logical, and physical data models that align with business requirements and compliance standards. Perform data profiling and analysis to understand data quality, structure, and relationships. Build and optimize data models to facilitate ingestion and transformation pipelines into warehouse utilizing Airflow, Dataflow, Pub / Sub, Spark, and Python. Manage and process structured and semi-structured data formats, including JSON and complex data types (e.g., Struct). Apply expertise in data modeling, database design, and data architecture to ensure scalability and performance. Collaborate with product managers and stakeholders to design data products that deliver actionable insights. Ensure and enforce data quality, lineage, and governance across all data assets. Define and document data models, relationships, pipelines, and processes to promote transparency and maintainability. POSITION SPECIFICATIONS : Bachelor s or master s degree in computer science, Data Engineering, Information Systems, or related STEM field. 5+ years of experience in data modeling, data governance and data Architecture roles. Hands-on experience with Google Cloud Platform, BigQuery, Dataflow, SQL, and Python. Define domain relationships and build connected entity models Strong understanding of normalization, dimensional modeling, and data warehousing. Familiarity with structured and semi-structured data handling. Attention to detail to ensure the accuracy of the data models and their ability to meet organizational needs. Understanding of retail banking / Credit Card data domains and regulatory requirements. Proficiency in SQL and data modeling tools (e.g., Wherescape, ERwin, ER / Studio) Excellent communication and documentation skills. Nice to Have : Certifications in Google Cloud Platform Professional Data Engineer or Architect. Experience with data governance frameworks and metadata management. Exposure to data product lifecycle and data mesh principles. Experience with ER.