Business Intelligence Engineer II, WFS Product and Analytics

Key job responsibilities

• Developed automated reporting solutions using QuickSuite and SQL to support global tier 1 associate hiring operations impacting 1M+ hires and 5M+ applications annually across NA, EU, APAC, and LATAM.
• Built dynamic dashboards tracking hiring funnel performance, cost per hire models, and fill rate metrics across multiple regions and business lines.
• Built and maintained orchestration layers automating multiple processes. Created systems to automate WBR/MBR/QBR reporting content, manual data entry, and pipeline error correction at scale.
• Drove global standardization of metrics and reporting across the workforce staffing portfolio.
• Extracted, transformed, and analyzed large datasets using SQL to identify optimization opportunities in recruitment processes. Developed complex queries for funnel analysis, workforce planning, risk detection, and early attrition signals enabling faster intervention on quality-of-hire indicators.
• Managed stakeholder relationships with regional hiring managers, HR business partners, operations leaders, and executive teams across four geographies. Translated complex analytical insights into actionable recommendations tied to organizational "Must Win" goals including capped fill rate, cost per hire reduction, and quality of hire improvement.

About the team

The Funnel Excellence Reporting (FER) team provides operationalized reporting, actionable insights, and tools for our business partners to improve the efficiency and quality of tier-one hiring worldwide. We provide accurate and timely reporting and analysis for various new processes and initiatives to WFS leadership in order to support data-driven decision-making which drives our business.

Team Tenets

• We focus on opportunities over problems.
• The speed of business matters.
• We are continuously skeptical of the metrics and products we build.
• We build for actionability and sustainability.
• We invest in our team.

Basic Qualifications

• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
• 1+ years of SQL, ETL or Oracle experience
• 1+ years of processing large, multi-dimensional datasets from multiple sources experience
• 1+ years of performing statistical analysis experience
• 1+ years of developing automated reporting experience
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with data modeling, warehousing and building ETL pipelines
• Experience in Statistical Analysis packages such as R, SAS and Matlab
• Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Preferred Qualifications

• Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
• Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets