[Remote] Risk Data AI/ML Engineer

Job Summary

SoFi, a leading financial services company, is seeking a Senior Data Engineer to join their remote Risk Data Engineering team. This role is open to candidates in the USA and involves leading technical efforts in building and maintaining data systems crucial for risk decision-making.

Responsibilities

• Technical Leadership: Serve as the technical lead for the Risk Data Engineering team, owning architectural decisions and data modeling strategy within the Risk domain.
• Standards & Architecture: Define naming conventions, modeling standards, and a layered dbt architecture (staging → intermediate → marts). Lead architecture discussions and technical planning.
• Code Quality: Conduct code reviews focusing on maintainability, readability, and scalability.
• Deliverables: Translate business priorities into production-ready technical solutions.
• Data Modeling & Pipelines:
  • Design and build production-grade Snowflake data models.
  • Develop scalable dbt projects with reusable macros and testing frameworks.
  • Manage Apache Airflow DAGs, ensuring idempotency, retry logic, and failure handling.
  • Implement CI/CD best practices for dbt and data pipelines.
  • Drive automation to reduce operational overhead.
  • Design dimensional and relational models aligned with business definitions, applying best practices for grain, SCD strategies, and surrogate keys.
  • Balance normalization and performance trade-offs, evolving models safely.
  • Ensure clear documentation of models, including lineage and business logic.
• Testing & Monitoring:
  • Own the dbt testing framework (schema, custom, generic tests).
  • Define and enforce freshness checks, SLA standards, and row-count validations.
  • Implement monitoring and observability using DataDog.
  • Proactively identify and reduce reliability incidents.
  • Establish measurable data quality SLAs with stakeholders.
• Team Development & Culture:
  • Participate in hiring, onboarding, and team building.
  • Run regular 1:1s and provide structured performance feedback.
  • Develop engineers towards ownership and technical growth.
  • Address underperformance constructively.
  • Foster a culture of accountability, documentation, and engineering excellence.
• Stakeholder Collaboration:
  • Partner with Risk Data Product Managers, Data Science, ML, and business stakeholders.
  • Communicate modeling decisions, trade-offs, and pipeline health clearly.
  • Influence cross-functional technical direction.
• System Maintenance & Governance:
  • Maintain scalable, secure data systems aligned with enterprise governance standards.
  • Improve documentation practices (runbooks, architecture decision records).
  • Contribute to workforce planning and technical roadmap discussions.

Skills & Qualifications

• Education: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience).
• Experience:
  • 8+ years of hands-on data engineering experience.
  • 2+ years of experience in a tech lead or formal engineering leadership role.
  • Deep expertise in dimensional and relational data modeling (SCD strategies, grain design).
  • Advanced dbt experience (layered architecture, macros, advanced testing, semantic layer).
  • Strong hands-on Snowflake experience (modeling, performance optimization).
  • Production-level experience managing Apache Airflow DAGs.
  • Advanced SQL skills (query optimization, performance tuning).
  • Strong Python skills for data pipeline development and automation.
  • Demonstrated ownership of a data quality and monitoring framework.
  • Experience in regulated or high-accuracy environments.
  • Experience with hiring, onboarding, and performance management.
  • Experience with Snowflake advanced capabilities (Snowpark, Cortex AI, ML functions).
  • Familiarity with LLM tooling, RAG systems, or AI-assisted data workflows.
  • Financial services experience (Credit, Fraud, Collections).
  • AWS experience (S3, Glue, Lambda) and infrastructure-as-code familiarity.
  • Experience implementing data governance frameworks at scale.
• Communication: Strong communication skills and ability to influence cross-functional stakeholders.

Benefits

• Comprehensive and competitive benefits package.

Company Overview

SoFi is a dynamic financial services company offering lending and wealth management services since 2011. Headquartered in San Francisco, California, USA, it employs 1001-5000 individuals. Learn more at https://www.sofi.com.

H1B Sponsorship

SoFi has a history of offering H1B sponsorships. Please note this does not guarantee sponsorship for this specific role.