Senior Data Engineer- People Analytics
About The Position
SoFi is seeking a detail-oriented Senior Data Engineer to design, build, and maintain data pipelines and datasets supporting People functions such as recruiting, compensation, talent management, and learning and development. The role will improve data accessibility and help the People Team and business leaders make informed decisions using high-quality, reliable data. The engineer will develop production dbt models in Snowflake that integrate Workday and other People systems into well-modeled, documented datasets, including slowly changing dimensions for People history. They will operate Airflow workflows, manage data quality and observability, implement access controls, and maintain semantic models and AI agents to the same standards as data pipelines. The role works closely with engineering, analytics, data science, and business teams; supports governance, security, and compliance; and mentors other engineers.
Requirements
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
- At least 5 years of experience in data engineering and analytics technical strategy.
- Proficiency with Python, SQL, dbt, Airflow, and GitLab.
- Proficiency with relational and cloud database platforms such as Snowflake, Redshift, or GCP.
- Thorough knowledge of data modeling, database design, data architecture principles, data operations, and CI/CD.
- Strong analytical and problem-solving abilities, including the ability to simplify complex issues into actionable plans.
- Experience with sensitive or regulated data and access controls.
Nice To Haves
- Experience with AI agents or LLM-assisted analytics.
- Experience with the HR / People function.
Responsibilities
- Develop and maintain robust data pipelines and datasets.
- Build foundational data products for key business areas and enhance self-service data capabilities for the People Team.
- Design and build production dbt models in Snowflake integrating Workday and other People systems into documented datasets, including slowly changing dimensions for People history.
- Build and operate Airflow DAGs to ingest People systems data and orchestrate dbt runs, ensuring reliable and re-runnable loads.
- Own data quality and observability through dbt tests, freshness checks, row-count validation, and monitoring.
- Implement and maintain row-level security and access controls for People data in partnership with governance and security teams.
- Build and maintain semantic models and AI agents under the same modeling, access, and quality standards as pipelines.
- Collaborate with data engineers, People analysts, data scientists, and business stakeholders to turn requirements into production-ready deliverables and communicate technical trade-offs to non-technical partners.
- Enforce data governance policies and practices to maintain data integrity, security, and regulatory compliance.
- Mentor other engineers through code review, modeling standards, and technical guidance.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
