[Remote] Senior Manager, Data Engineering
Note: The job is a remote job and is open to candidates in USA. SoFi is a next-generation financial services company and national bank that is transforming personal finance. They are seeking a Senior Manager, Data Engineering to lead a team focused on data models and infrastructure critical to risk and AI applications in the banking sector.
Responsibilities
- 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, freshness SLAs, and anomaly detection to ensure reliability across all pipelines
- Stay 50% hands-on - write and review production code, own critical pipelines, and lead by example
Skills
- 15+ years of experience in data engineering, with the majority of that tenure inside US banks or financial institutions
- Deep knowledge of banking risk data domains - lending, credit risk, deposits, AML, KYC, fraud, banking regulations, and the critical datasets that support them
- Expert-level Snowflake, dbt, and Python - proven ability to design and own complex analytical data models; Python fluency for Airflow DAGs, pipeline logic, and data quality scripting
- Strong pipeline and infrastructure skills - hands-on experience with Airflow, MongoDB, and Terraform in production environments
- People leadership - experience managing and mentoring data engineers; strong code review culture
- Banking regulatory awareness - familiarity with BCBS 239, BSA/AML regulations, OCC/Fed/FDIC data expectations
- Communication - able to translate complex data concepts for risk, compliance, and executive stakeholders
- Experience at a US bank in Model Risk, Integrated Risk, ERM, or Compliance Analytics
- Familiarity with GRC platforms (ServiceNow) and risk data warehouses
- Experience with LLM/AI application data pipelines and observability tooling
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