Sofi · United States

Senior Manager, Data Engineering

🏢 Sofi📍 United States🕐 Posted 52 days ago
⏱ Full-timeRisk 2LOD✅ Direct from employer ATS
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About this role

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: SoFi is looking for a Senior Manager, Data Engineering to join our IRM Analytics team. This is a hands-on leadership role (50% individual contributor, 50% people manager) for a seasoned data engineering leader with deep roots in US banking and financial risk data

You will own the data models, data pipelines, and data infrastructure that underpin our risk and AI applications - spanning critical domains like lending, credit, fraud, AML, and compliance. You will lead a focussed team of data engineers, set technical direction, and be an integral contributor to every data and AI initiative we build

This role is for someone who has spent most of their career inside US banks and understands not just the technology, but the data - the domains, the regulatory context, the critical datasets, and why they matter

What you’ll do: Own the data model - design, build, and maintain integrated data models for lending, credit, fraud, AML, KYC, and related risk domains; ensure models reflect banking semantics and regulatory requirements Own the data pipeline and infrastructure - architect and manage end-to-end data pipelines using dbt, Airflow, Snowflake, MongoDB, and Terraform; ensure reliability, performance, and scalability Lead data and AI projects - serve as the data engineering anchor for all data and AI initiatives; partner with full stack engineers, AI/ML engineers, and product managers to deliver production-grade applications; own the data infrastructure for AI use cases including RAG pipeline data management and evaluation dataset / ground truth curation Lead a team of data engineers - manage and develop the team; set standards for code quality, code review, testing, documentation, and CI/CD practices for data pipelines Drive data quality and governance - establish data definitions, lineage, and quality standards aligned to regulatory expectations (BCBS 239, SR 11-7, etc.); implement data observability practices including dbt tests, data contracts, fresh

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