This role is foundational to our Consumer Group Risk (CG Risk) team's AI transformation strategy. You will design and build the data infrastructure - data dictionary, schema management, and pipelines - that directly powers AI agents and automated risk workflows across our consumer lending and banking products. Without this foundation, the team's AI capabilities cannot scale. We are seeking a Staff Fraud & Risk Analyst as part of our Consumer Risk Analytics team. The successful candidate will own the data layer that enables our analytics and AI applications, working across Fraud & Risk Policy, Credit Risk, Operations, Data Science, and Product. **Responsibilities** - Own and maintain the organization's risk data dictionary, metadata, data lineage, and governance standards across AWS and Google BigQuery, serving as the single source of truth for analytics and risk teams. - Design, build, and operate scalable data architecture, data marts, and pipelines that support consumer risk analytics, power AI agents, and enable automated risk workflows, while improving performance, efficiency, and scalability. - Partner with the AI architect, product, and technology teams to implement data-layer components and integrate new data sources and features into the broader risk and AI infrastructure. - Establish data quality processes, including validation, reconciliation, and monitoring, to ensure data is accurate, consistent, and accessible. - Collaborate effectively with data scientists, analysts, and business stakeholders to translate requirements into efficient data models and ETL processes, demonstrating sound judgment, strategic thinking, creativity, and the ability to manage multiple priorities. **Qualifications** - Bachelor's degree in Computer Science, Information Systems, Engineering, or another quantitative field with at least 5 years of relevant experience; or a master's degree or higher in a related field with at least 3 years of relevant experience in data engineering, data architecture, or data warehousing. - Strong analytical skills and business acumen, with experience in financial services, FinTech, consumer risk, or risk-related KPIs and OKRs preferred. Experience building data infrastructure for AI and LLM applications, including agent-ready schema documentation, vector stores, or RAG pipelines is a strong plus. - Advanced Python and distributed data-processing skills, including experience with Spark, Spark SQL, or Scala, combined with hands-on expertise in Databricks and Google BigQuery. Demonstrated experience designing scalable data marts, data warehouses, or data lakes using sound data-modeling and dimensional-modeling principles is required. Familiarity with Snowflake, AWS S3, or other cloud data platforms is a plus. - Strong written and verbal communication skills, with the ability to explain complex technical concepts clearly to both technical and non-technical stakeholders. - Highly accountable, organized, collaborative, and empathetic, with a passion for building robust data foundations, curiosity about complex business problems, and the ability to balance immediate priorities with long-term strategic considerations in a fast-paced environment. Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Mountain View $176,500 - $238,500