Staff Risk AI & Data Engineer

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role: We are seeking a Staff Risk AI & Data Engineer to lead a high-performing engineering pod and drive technical excellence, operational maturity, and AI-enabled engineering practices across the broader Risk Data organization. This is a senior technical leadership role focused on scaling modern data platforms, AI-native engineering workflows, and organizational standards across multiple teams. You will lead through technical strategy, process optimization, team development, and scalable framework creation while partnering closely with engineering leadership, product, compliance, infrastructure, analytics, and external vendors. The ideal candidate combines strong leadership and team calibration experience with deep expertise across Snowflake, dbt, Python, Airflow, and modern AI-enabled engineering workflows. This role requires a hands-on technical leader who can challenge architectural decisions, improve operational efficiency, and help shape the long-term direction of SoFi’s Risk Data ecosystem. What you’ll do: Lead, mentor, calibrate, and upskill a high-performing pod of data engineers while raising the technical and operational bar across the broader Risk Data organization. Conduct regular skills assessments, identify development gaps, and create targeted growth plans to strengthen engineering capabilities and support long-term succession planning. Establish measurable ownership frameworks, delivery KPIs, and operational standards that improve accountability, scalability, and engineering quality. Champion AI-native engineering workflows across the organization, including AI-assisted development environments, intelligent alerting and triage systems, automated documentation, and AI-powered operational tooling. Standardize and optimize engineering and data delivery processes across multiple teams to improve predictability, scalability, and delivery efficiency. Design and implement scalable frameworks, templates, and standards across onboarding, incident response, semantic layers, dbt modeling, observability, governance, and data validation practices. Provide technical leadership across Snowflake platform architecture, dbt transformation strategy, Airflow orchestration, AI-enabled workflows, and enterprise-scale data platform governance. Review and challenge technical strategies, pipeline architectures, and implementation plans to ensure long-term scalability, reliability, compliance, and operational maturity. Ensure strong governance, security, lineage, observability, and compliance standards across production data systems and AI-enabled workflows. Serve as the primary technical liaison for strategic vendor and platform relationships, including Snowflake, credit bureau providers, governance tooling vendors, and AI/data platform partners. Partner with vendors on platform optimization, feature adoption, integration strategy, SLA management, and operational scalability initiatives. Collaborate closely with platform engineering, infrastructure, compliance, analytics, and model risk teams to align Risk Data initiatives with broader enterprise strategy. Evaluate emerging AI and data technologies, including AI-powered ETL, intelligent monitoring systems, and LLM-enabled operational tooling, and make strategic build-versus-buy recommendations. Partner with Product Manage