Design, build, and operate data pipelines processing terabytes daily with Airflow and BigQuery
Own end-to-end data models and transformations for analytics and ML features
Build and maintain embedded analytics infrastructure for merchant data products
Evolve data platform on GCP with BigQuery, Cloud SQL, AlloyDB, and CDC datastreams
Improve data quality and reliability with testing, observability, alerting, and validation
Own data lineage, metadata, and docs; prep data for agentic/LLM use with clear metrics

🎯 Requirements

5–8 years building and operating production data systems
Strong SQL, proficient in Python; comfortable building APIs
Worked with modern cloud data stacks (GCP preferred; AWS or Azure transfers well)
Understand dimensional modeling and slowly changing dimensions
Emphasize data quality, lineage, observability as core engineering concerns
Communicate clearly across technical and non-technical teams

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