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SoFi is seeking a Principal Software Engineer to lead the Data Trust pillar within the Data Platform Group. This is a hands-on individual contributor role with broad organizational impact, responsible for designing, building, and operating distributed systems and reusable platform primitives that enforce data quality, privacy, metadata, lineage, access controls, and reliability across the enterprise.
You will work across three connected areas: establishing shared Data Trust capabilities, raising reliability of data in batch and low-latency environments, and applying those foundations to a semantic context layer for trusted analytics and AI. By making business meaning, ownership, provenance, quality, freshness, and access policies machine-readable, you will help end users and AI systems work from consistent, governed context.
Key responsibilities include:
- Define and execute technical direction for data contracts, metadata and catalog modernization, lineage, data quality, privacy, and access controls
- Build platform services, libraries, and reference patterns that make contracts, quality rules, privacy policies, and access requirements versioned, testable, observable, and automatically enforceable
- Establish technical foundations for a governed semantic context layer connecting business definitions, metadata, lineage, ownership, quality, freshness, and access policy
- Lead evolution of Data Trust capabilities across Snowflake, AWS data services, Kafka-based ingestion, and other batch or low-latency environments
- Raise production data systems standards through observability, integrity checks, audit evidence, incident learning, and safe automation
- Drive multi-quarter cross-organizational initiatives, earning alignment on architectural tradeoffs and investment decisions
Success in the first 12–18 months includes: clear enterprise architecture for Data Trust primitives; materially improved coverage, observability, SLOs, and automated enforcement in priority data domains; production-ready patterns for governing data in batch and low-latency environments; initial semantic context capabilities operating in production; measurably reduced manual investigation and compliance evidence-gathering; and adoption of reusable standards by engineering and partner teams.
REQUIREMENTS:
- 15+ years of software or data engineering experience (or 13+ years with a Master's degree) with proven track record designing, building, and operating distributed data platforms at enterprise scale
- Deep experience designing horizontal, multi-tenant platform services that other engineering teams depend on; understanding of distributed systems failure modes, eventual consistency, and latency/availability/cost tradeoffs
- Practical, battle-tested experience building or managing components of the modern data trust stack: data contracts, metadata catalogs, data quality frameworks, end-to-end lineage, fine-grained access control (RBAC/ABAC)
- Advanced knowledge of modern data ecosystems, specifically Snowflake, Kafka (or similar streaming platforms), and AWS data services; ability to govern data in motion and at rest
- Mastery of one or more core programming languages (Python, Java, Go) and advanced SQL; comfortable writing production-grade code, conducting rigorous code reviews, building declarative infrastructure (Terraform, CI/CD)
- History of successfully driving multi-team, cross-functional technical initiatives; ability to build consensus across Engineering, Security, Privacy, and Product teams
- Experience managing Tier-0/mission-critical infrastructure with "trust but verify" mindset, relying on automated testing, drift detection, and circuit breakers
NICE TO HAVE:
- FinTech or regulated industry experience where auditability, data privacy (CCPA/GDPR), and data integrity are architectural requirements
- Experience building semantic layers, knowledge graphs, or context engines that ground LLMs and autonomous agents in governed enterprise data
- Contributions to relevant open-source data or metadata projects (Apache Iceberg, OpenMetadata, DataHub, Amundsen)
