Senior Fraud Data Engineer: Snowflake, dbt & Pipelines

SoFi; Cottonwood Heights (UT); On-site; USD 120,000 - 200,000; Full time

Job summary

SoFi is seeking a Senior Data Engineer to design, build, and scale data infrastructure powering the Fraud CoE analytics. You will consolidate data pipelines from multiple source systems into governed Snowflake data marts, and enable leadership reporting with timely, reliable data.

This role requires partnering with Fraud Data Engineering, analytics teams, and platform squads to deliver scalable solutions and maintain strong data governance.

Qualifications

• 4+ years of data engineering experience with strong hands-on expertise in SQL, Python, and cloud data warehouse platforms.
• Proven experience building and maintaining production-grade data pipelines using modern data stack tools (dbt, Airflow, or equivalent).
• Strong data modeling skills — experience designing analytical data structures optimized for reporting and self-service consumption.
• Ability to work closely with analytics and business stakeholders to translate requirements into scalable data solutions.
• Strong documentation habits and commitment to data quality, testing, and pipeline reliability.
• Exposure to dbt Cloud, Airflow/MWAA, or similar orchestration platforms.

Responsibilities

• Design, build, and maintain scalable data pipelines that consolidate fraud operational data from multiple source systems into governed Snowflake data marts.
• Partner with Fraud Data Engineering and the TDM platform team on the foundational Fraud CoE data buildout, including summarized metric tables that standardize reporting across all fraud product lines.

Skills

SQL

Python

Snowflake

Data modeling

Data governance

Stakeholder collaboration

Tools

dbt

Airflow

MWAA

Job description

SoFi is seeking a Senior Data Engineer to design, build, and scale data infrastructure powering the Fraud CoE analytics. You will consolidate data pipelines from multiple source systems into governed Snowflake data marts, and enable leadership reporting with timely, reliable data.

This role requires partnering with Fraud Data Engineering, analytics teams, and platform squads to deliver scalable solutions and maintain strong data governance.