Support Ecosystem Analytics: Own the reporting and optimization of Case Volume and Resolution Rates. You will identify bottlenecks in our support funnel and recommend strategies to decrease "Time to Resolve."
Platform Vigilance: Monitor real-time data to detect site issues or technical anomalies that impact user experience, acting as the bridge between Client Ops and Engineering for rapid incident response.
Fraud & Risk Mitigation: Develop and maintain dashboards to track suspicious activity and fraud patterns, ensuring the platform remains secure for all legitimate users.
Operational Intelligence: Use Tableau to build comprehensive visualizations that allow leadership to see "at a glance" how effectively we are serving our clients and where the biggest operational risks lie.
Root Cause Analysis: Investigate why certain issues recur. You won’t just report that volume is up; you’ll identify if it’s a product bug, a training gap, or a seasonal trend.
Data Pipeline Advocacy: Partner with Data Engineering to ensure that data from our support tools and site logs are correctly ingested into Snowflake for deep-dive analysis.
Strategic Recommendations: Translate complex operational data into clear, high-impact insights for senior leadership, focusing on how to scale our service model without increasing headcount linearly.

Experience: 5+ years of experience as a Data Analyst, with a heavy focus on Operations, Trust & Safety, or Customer Support Analytics.
Visualization Expert: High proficiency in Tableau or Hex is preferred. You should be able to turn messy operational logs into clean, actionable dashboards.
SQL Power User: Advanced ability to write complex SQL queries to join disparate datasets (e.g., matching support tickets to platform usage logs).
Fraud & Risk Mindset: Experience identifying anomalies or patterns associated with fraud or platform abuse is a significant plus.
Problem Solver: An inquisitive mindset; when you see a spike in "Resolution Time," you don't stop until you find the technical or process-driven "why."
Education: Bachelor’s degree in a quantitative field (Statistics, Economics, Data Science, etc.).

Compensation: Competitive base pay tied to role and experience, with opportunities for bonuses, commissions, and equity.
Benefits: Check out our full list at http://engine.com/culture.
Environments for Success: Different roles have different needs in terms of the environments that drive success which is why we have a hybrid-hub model. Whether you are in one of our amazing offices or fully remote, we’ll make sure you have what you need to succeed.

Senior Data Analyst, Client Ops

Key skills