Senior Data Engineer - Risk & Predictive Analytics

Google; Town of Montana (WI); On-site; USD 136,000 - 226,000; Full time

Job summary

Google | gTech Risk is seeking a Senior Data Engineer in Chicago, IL to design data pipelines and risk models powering the risk graph. You will implement automated risk indicators, merge operational data with enterprise risk platforms, and collaborate with Data Science and Engineering to shift from reactive to predictive risk analysis.

The role requires mid-level experience, strong data engineering skills, and the ability to deliver scalable analytics across Google’s risk workflow.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (DataFlow, Spark, etc.).
• Experience with Python or R for statistical analysis and model development.
• Experience in SQL and data visualization tools (e.g., Tableau, Looker).

Responsibilities

• Develop and maintain the data architecture and predictive models powering gTech's risk graph.
• Design and deploy automated key risk indicators (rKRIs) across all gTech workflows, replacing manual, point-in-time reporting.
• Integrate gTech operational data with central enterprise risk platforms to create a single, automated source of truth.
• Partner with core Data Science and Engineering teams to transition our risk analysis from reactive (incident based) to predictive (threat based).
• Build and manage executive dashboards for business reviews, pipeline management, and enterprise risk posture reporting.

Skills

Data pipelines

Data modeling

Python or R

SQL & visualization

Education

Bachelor's degree

Tools

Flume

DataFlow

Spark

Job description

Google | gTech Risk is seeking a Senior Data Engineer in Chicago, IL to design data pipelines and risk models powering the risk graph. You will implement automated risk indicators, merge operational data with enterprise risk platforms, and collaborate with Data Science and Engineering to shift from reactive to predictive risk analysis.

The role requires mid-level experience, strong data engineering skills, and the ability to deliver scalable analytics across Google’s risk workflow.