Data Engineer I, Payment Acceptance & Experience

Job summary

DESCRIPTION The Payment Acceptance & Experience team is looking for a Data Engineer with a deep understanding of the full life-cycle of data generation and application. Our team is responsible for how Amazon's customers pay on Amazon's sites and through Amazon's services around the globe.

Benefits

Qualifications

• The Payment Acceptance & Experience team is looking for a Data Engineer with a deep understanding of the full life-cycle of data generation and application.
• into robust, scalable solutions that fit the overall data architecture.
• Build data quality and controllership checks for completeness, freshness, and lineage on the datasets behind key business metrics, and design alerting and triage paths.
• Contribute to AI-native engineering infrastructure by building scaffolding, guardrails, and observability for AI agents that automate Data Engineering workflows.
• Migrate legacy datasets onto a centralized data platform with parallel-run validation, downstream consumer coordination, and catalog updates.
• Maintain a semantic layer that maps business terms to physical data structures, so human users and AI agents understand the data they query.
• Analyze source data systems and drive best practices in source teams.
• Participate in the full development life cycle: design, implementation, testing, documentation, delivery, support, and maintenance.
• Produce comprehensive, usable dataset documentation and metadata.
• Evaluate dataset implementations and recommend new or existing software products and
• 2+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines

Responsibilities

• Our team is responsible for how Amazon's customers pay on Amazon's sites and through Amazon's services around the globe.
• As a Data Engineer I, you will design, develop, implement, test, and operate large-scale, high-volume, high-performance data structures for analytics, reporting, and machine learning.
• You will leverage your expertise in data pipelines and persistence to build systems and
• Implement real-time and batch data ingestion routines using best practices in data modeling.
• Develop ETL/ELT processes using AWS

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