Are you a skilled data professional with a passion for transforming raw data into actionable insights and a proven track record of learning and implementing new technologies? The Finance Data & Insights Team is an agile product team responsible for the development, production, and transformation of financial data and reporting across Consumer Community Banking. Our vision is to enhance the lives of our people and increase the firm's value by leveraging data and advanced tools to analyze information, generate insights, save time, improve processes and controls, and lead the organization in developing future-ready skills.

• As a Data Domain Architect Associate in the Consumer Community Banking
• Auto Finance Data & Insights Team, you will assist in the development, testing and on-going maintenance of finance data products for the Auto Finance line of business. You will focus on understanding data requirements, developing proof of concept data against requirements, comparing data sources, testing solutions, as well as preparing ad hoc analysis for our CFO (Chief Finance Officers) stakeholders.

Job Responsibilities:

• Design and implement comprehensive and efficient data mart schemas that consolidate key data categories from various source systems, tailored to the needs of the Auto Finance & Business Management functions.
• Collaborate with Business stakeholders to understand requirement and accordingly map source & calculation logic
• Collaborate with cross-functional teams, including data engineers, data analysts, and technical specialists, to gather and analyze business requirements.
• Develop, implement, and optimize data workflows, Extract Transform Load (ETL) processes, and data pipelines using Databricks.
• Utilizing Databricks and Thought Spot tools, create a robust and efficient reporting environment for PXT Finance data analytics and reporting.
• Work closely with your business domain Product teams and business stakeholders to: 1) design and develop insightful reporting and analytics solutions that drive informed decision-making; 2) apply design led thinking to meet their needs, including making data discoverable and accessible for analytical needs.
• Maintain up-to-date documentation on data mart architecture, data models, ETL processes, and data governance policies.
• Partner with product managers, engineers, and functional experts across the end‑to‑end AI/ML lifecycle—conception, validation, scaling, production delivery, and performance monitoring.
• Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences.
• Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.

Required qualifications, capabilities and skills :

• Overall 6 years of experience in Data Management, data Engineering, data lineage, data dictionaries, and making data discoverable
• Strong knowledge and experience with data Engineering, data lineage, data dictionaries, and making data discoverable
• Familiarity with data architecture, data warehousing, and data integration, with a focus on the retail banking or financial services industry.
• Expertise in designing and implementing scalable and efficient data mart architectures, including star schema, snowflake schema, and other data modeling techniques.
• Understanding of agentic AI systems and their design principles.
• Bachelor’s degree in Computer Science, Information System, or related discipline
• Experience with Databricks, Snowflake, or other Cloud Data Warehouse, Data Engineering, Data Modeling, ERWIN
• Proven track record of successfully managing and delivering complex data projects in a fast-paced, dynamic environment.
• Thought Spot, Tableau, Alteryx, or Essbase experience