Principal Software Engineer, Data Platform — Data Trust & AI Context

Posted 48 Minutes Ago
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3 Locations
Hybrid
198K-341K Annually
Expert/Leader
Fintech • Mobile • Software • Financial Services
SoFi’s mission is to help people reach financial independence to realize their ambitions.
The Role
Provides hands-on technical leadership for enterprise Data Trust platforms. Designs and operates distributed systems supporting data contracts, metadata, lineage, quality, privacy, access controls, reliability, and semantic context for analytics and AI. Leads batch and streaming capabilities across Snowflake, AWS, and Kafka; establishes observability, SLOs, automated enforcement, and operational rigor. Drives cross-functional architecture and multi-quarter initiatives while mentoring engineers and building reusable platform standards.
Summary Generated by Built In

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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’s ability to deliver trusted member experiences, manage risk, meet regulatory obligations, and scale enterprise AI depends on data that is reliable, governed, understandable, and available when it is needed.

As a Principal Software Engineer in the Data Platform Group, you will provide hands-on technical leadership within the Data Trust pillar. Working alongside the Senior Manager and other Principal Engineers, you will design, build, and operate the distributed systems and reusable platform primitives that make data quality, privacy, metadata, lineage, access, and reliability enforceable by construction across the enterprise.

Your work will span three connected areas: establishing shared Data Trust capabilities, raising the reliability of data across 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.

This is an individual contributor role with broad organizational impact. You will personally contribute code, prototypes, architecture, and operational improvements while setting technical direction across engineering, data, security, privacy, legal, risk, analytics, and product teams. You will build reusable enterprise capabilities and reference patterns that partner teams can adopt, while domain teams retain ownership of their application-specific use cases and serving paths.

What you will own:

  • Data Trust architecture and strategy: Define and execute the technical direction for data contracts, metadata and catalog modernization, lineage, data quality, privacy, and access controls. Translate business, regulatory, and engineering requirements into a coherent platform strategy and sequence investments for long-term impact.
  • Declarative enforcement primitives: Build platform services, libraries, and reference patterns that make contracts, quality rules, privacy policies, and access requirements versioned, testable, observable, and automatically enforceable across the data lifecycle.
  • Semantic context for analytics and AI: Establish the technical foundations for a governed semantic context layer that connects business definitions, metadata, lineage, ownership, quality, freshness, and access policy. Enable trusted discovery, analytics, and AI-assisted or agentic experiences without turning this role into a model-development function.
  • Reliability across batch and streaming data: Lead the evolution of Data Trust capabilities across Snowflake, AWS data services, Kafka-based ingestion, and other batch or low-latency environments. Establish explicit SLOs, failure modes, correction paths, and operational ownership, supported by automated detection, containment, remediation, and recovery.
  • Mission-critical operational rigor: Raise the standard for production data systems through observability, integrity checks, audit evidence, incident learning, and safe automation. Help move the organization from reactive troubleshooting and manual compliance activity toward proactive, measurable control.
  • Cross-organizational technical leadership: Drive multi-quarter initiatives across teams and functions, earning alignment on difficult architectural tradeoffs and investment decisions. Serve as a trusted technical authority for Data Trust while mentoring senior engineers, strengthening design and implementation practices, and raising the broader engineering bar.
What success looks like in the first 12–18 months:
  • A clear enterprise architecture and delivery path exists for Data Trust primitives spanning contracts, metadata, lineage, quality, privacy, and reliability.
  • Priority data domains have materially improved coverage, observability, SLOs, and automated enforcement.
  • The platform provides production-ready patterns for governing data in both batch and low-latency environments.
  • Initial semantic context capabilities are operating in production and provide more reliable, traceable context for analytics and AI use cases.
  • Manual investigation, recurring data failures, and compliance evidence-gathering are measurably reduced.
  • Engineering and partner teams have adopted reusable standards and capabilities rather than creating isolated point solutions.
What you’ll need:
  • Experience & Education: 15+ years of software or data engineering experience (or 13+ years with a Master’s degree) with a proven track record of designing, building, and operating distributed data platforms at enterprise scale.
  • Platform Architecture Expertise: Deep experience designing horizontal, multi-tenant platform services that other engineering teams depend on. You understand the failure modes of distributed systems, eventual consistency, and how to balance latency, availability, and cost.
  • Data Trust & Governance Depth: Practical, battle-tested experience building or managing components of the modern data trust stack, such as data contracts, metadata catalogs, data quality frameworks, end-to-end lineage, and fine-grained access control (RBAC/ABAC).
  • Batch & Streaming Mastery: Advanced knowledge of modern data ecosystems, specifically Snowflake, Kafka (or similar streaming platforms), and AWS data services. You know how to govern data in motion just as effectively as data at rest.
  • Hands-On Engineering: Mastery of one or more core programming languages (e.g., Python, Java, Go) and advanced SQL. You are comfortable writing production-grade code, conducting rigorous code reviews, and building declarative infrastructure (Terraform, CI/CD).
  • Cross-Organizational Leadership: A history of successfully driving multi-team, cross-functional technical initiatives. You know how to build consensus across Engineering, Security, Privacy, and Product teams, translating compliance and risk requirements into frictionless engineering primitives.
  • Operational Rigor: Experience managing Tier-0/mission-critical infrastructure. You build systems with a "trust but verify" mindset—relying on automated testing, drift detection, and circuit breakers rather than manual processes.

Nice to have:

  • FinTech / Regulated Industry Experience: Prior experience operating in a highly regulated environment where auditability, data privacy (CCPA/GDPR), and data integrity are architectural requirements, not afterthoughts.
  • AI Infrastructure Exposure: Experience building semantic layers, knowledge graphs, or context engines that ground LLMs and autonomous agents in governed enterprise data.
  • Open Source Contributions: Contributions to relevant open-source data or metadata projects (e.g., Apache Iceberg, OpenMetadata, DataHub, Amundsen).
Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. 
 
To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.The Company hires the best qualified candidate for the job, without regard to protected characteristics.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.New York applicants: Notice of Employee RightsSoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email [email protected].We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time.
Internal Employees
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Skills Required

  • 15+ years of software or data engineering experience, or 13+ years with a Master's degree
  • Experience designing, building, and operating distributed data platforms at enterprise scale
  • Deep experience designing horizontal, multi-tenant platform services
  • Practical experience with data contracts, metadata catalogs, data quality frameworks, end-to-end lineage, and fine-grained access control
  • Advanced knowledge of Snowflake, Kafka or similar streaming platforms, and AWS data services
  • Mastery of one or more core programming languages such as Python, Java, or Go
  • Advanced SQL proficiency
  • Experience building declarative infrastructure with Terraform and CI/CD
  • History of driving multi-team, cross-functional technical initiatives
  • Experience managing Tier-0 or mission-critical infrastructure
  • FinTech or regulated industry experience, including CCPA or GDPR exposure
  • Experience building semantic layers, knowledge graphs, or context engines for governed enterprise data
  • Contributions to relevant open-source data or metadata projects

What the Team is Saying

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SoFi Compensation & Benefits Highlights

  • Healthcare Strength — Health coverage is described as comprehensive—medical, dental, vision, and mental-health support. Materials also indicate high employer premium contributions on core plans, enhancing overall value.
  • Parental & Family Support — Offerings include fully paid parental leave and extensive family benefits such as fertility, adoption resources, parenting support, and backup childcare/eldercare. Paid caregiver leave and related supports are also highlighted.
  • Affordable Benefits — Materials indicate the company covers most or all medical premiums on certain plans, helping keep employee premium costs low. HSA/FSA options further support affordability.

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The Company
HQ: San Francisco, CA
4,500 Employees
Year Founded: 2011

What We Do

SoFi wasn’t built to be a bank. Or a technology company. We were built for one mission: help people achieve financial independence so they can realize their ambitions. Redefining an entire industry isn’t easy work—and it’s not for the faint of heart. It takes a certain kind of team. People with diverse perspectives and expertise, united by a common sense of purpose. People willing to challenge assumptions but always do the right thing. People proving that innovation and responsibility don’t have to compete, but can come together to create something truly unconventional in the world. For the last eight years, we’ve been charting this new path forward. We call it The SoFi Way. At SoFi, we don’t just talk about culture: we live it. The SoFi Way is how we show up every day, how we make decisions, and how we build for our members, clients, and each other.

Why Work With Us

Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation Fintech company using innovative, mobile-first technology to help our members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront.

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Employees engage in a combination of remote and on-site work.

For the majority of our workforce who work on a hybrid schedule, the in-office requirement is a handful of days per month!

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