Head of People Analytics Data Engineering

SoFi; San Francisco (CA); On-site; USD 180,000 - 230,000; Full time

Job summary

SoFi is seeking a data engineering leader to drive People Analytics, including AI-assisted workforce analytics on Snowflake. This player-coach role blends hands-on coding with people leadership, partnering with analytics, data science, and business stakeholders to deliver scalable, trusted workforce insights.

You will design durable data models and pipelines, enforce governance, and guide a team of engineers to produce production-ready results while balancing speed with quality and compliance.

Qualifications

• A bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
• 7+ years in data engineering, analytics engineering, or data platform engineering.
• 5+ years managing or formally leading engineers.
• Proficiency in data engineering tech stack: Python / SQL / dbt / Airflow / Gitlab.
• Experience designing dimensional models, semantic layers, data marts, or analytical data products.
• Experience with data quality, testing, lineage, observability, and production support.
• Strong ability to translate business needs into technical architecture.
• Experience with sensitive or regulated data and access controls.
• Proven ability to coach engineers and build healthy technical culture.
• Strong communication with technical and non technical stakeholders.
• Proficiency in 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.

Responsibilities

• Manage, coach, and grow a team of data engineers.
• Set expectations for quality, collaboration, delivery, and technical ownership.
• Create a strong engineering culture where people solve hard problems, move quickly, and enjoy the work.
• Collaborate with cross-functional teams, such as other data engineers, people analysts, data scientists, and business stakeholders, to translate requirements into production-ready deliverables, and communicate technical trade-offs to non-technical partners.
• Write and review production code.
• Lead design reviews, code reviews, and technical problem solving.
• Step into critical pipelines, models, or AI workflows when needed.
• Design and maintain sustainable data models, pipelines, semantic layers, and testing frameworks.
• Establish team practices for documentation, lineage, data quality, and observability.
• Set standards for SQL, Python, dbt, Airflow, Snowflake, testing, documentation, CI/CD, and release management.
• Ensure the team ships work that is reliable, maintainable, secure, and understandable.
• Enforce data governance policies and practices to maintain data integrity, security, and compliance with relevant regulations.
• Own technical delivery for AI-assisted workforce analytics and internal tools.
• Translate business needs into scalable technical designs, delivery plans, and engineering milestones.
• Partner with People Analytics, People leaders, Legal, Compliance, and other stakeholders to deliver trusted workforce insights.
• Partner on semantic models, evaluation datasets, testing, and quality controls for AI-assisted analytics
• Create enough process to protect quality, privacy, and trust for sensitive People data without slowing the team unnecessarily.

Skills

Data engineering

People management

Python

SQL

dbt

Airflow

Communication

Education

Bachelor’s degree in Computer Science, Data Science, Engineering, or related field

Tools

Snowflake

Redshift

GCP

Gitlab

Job description

SoFi is seeking a data engineering leader to drive People Analytics, including AI-assisted workforce analytics on Snowflake. This player-coach role blends hands-on coding with people leadership, partnering with analytics, data science, and business stakeholders to deliver scalable, trusted workforce insights.

You will design durable data models and pipelines, enforce governance, and guide a team of engineers to produce production-ready results while balancing speed with quality and compliance.