Engineering Manager, AI-Powered People Analytics

SoFi

United States

On-site

USD 150,000 - 190,000

Full time

14 days+

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Job summary

SoFi is seeking an experienced Data Engineering lead for People Analytics to drive AI-assisted workforce analytics on Snowflake. This player-coach role combines hands-on engineering with people leadership, partnering with stakeholders to deliver reliable, scalable analytics platforms.

You will design data models and pipelines, establish governance and observability, and mentor engineers to ship high-quality, compliant solutions at scale.

Qualifications

  • Bachelor’s degree in CS, DS, Engineering or related field.
  • 7+ years in data engineering/analytics engineering/ data platform engineering.
  • 5+ years managing engineers.
  • Proficiency in Python/SQL/dbt/Airflow/Gitlab.
  • Experience designing dimensional models/semantic layers/data marts.
  • Experience with data quality, lineage, observability, and production support.
  • Strong ability to translate business needs into technical architecture.
  • Experience with sensitive or regulated data and access controls.
  • Proven coaching ability and strong communication with tech and non-tech stakeholders.
  • Proficiency with Snowflake/Redshift/GCP.

Responsibilities

  • Lead and develop a team of data engineers.
  • Set quality, collaboration, delivery, and technical ownership expectations.
  • Build scalable data foundations, pipelines, and semantic layers.
  • Own engineering standards for SQL, Python, dbt, Airflow, Snowflake, CI/CD.
  • Deliver AI-enabled workforce analytics and internal tools.
  • Balance speed with governance to protect sensitive People data.

Skills

Python
SQL
dbt
Airflow
Gitlab
Communication

Education

Bachelor's degree in Computer Science, Data Science, or Engineering

Tools

Snowflake
Redshift
GCP
Snowflake Cortex AI
Streamlit

Job description

SoFi is seeking an experienced Data Engineering lead for People Analytics to drive AI-assisted workforce analytics on Snowflake. This player-coach role combines hands-on engineering with people leadership, partnering with stakeholders to deliver reliable, scalable analytics platforms.

You will design data models and pipelines, establish governance and observability, and mentor engineers to ship high-quality, compliant solutions at scale.

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