Lead Data Engineer, Customer Identity Analytics

Summary

Technical lead for the Customer Identity team responsible for setting technical direction and owning the lifecycle of the identity platform. This role is hands‑on with customer recognition systems, data quality analysis, and platform modernization while guiding a small team of engineers. The position is hybrid based in Seattle, WA and focuses on improving match accuracy and building reliable identity infrastructure.

• Own strategy to improve customer recognition accuracy through partner collaboration and data enrichment pilots
• Collaborate with analytics and business stakeholders to support use cases like marketing measurement and personalization
• Design and implement platform quality KPIs, match confidence scoring, and precision/recall metrics
• Lead migration to a warehouse-native architecture (Big Query + dbt) to reduce operational overhead
• Mentor and develop engineers, set technical standards, and run design reviews
• Build automated data quality checks and monitoring to prevent downstream regressions

• 7+ years of experience in data engineering, applied data science, or ML with hands‑on work in entity resolution or customer identity systems at scale
• Deep understanding of data matching concepts including blocking, match rules, confidence thresholds, and precision/recall tradeoffs
• Production-quality SQL skills and experience with Big Query or comparable cloud data warehouses
• Hands‑on experience with dbt, Airflow or equivalent transformation/orchestration frameworks
• Ability to frame ambiguous data quality problems as measurable experiments and communicate statistical concepts to stakeholders