Senior Data Engineer, Global Selling
5 days ago
Key job responsibilities
- Architect and implement a scalable, cost-optimized S3-based Data Lakehouse that unifies structured and unstructured data from disparate sources.
- Establish metadata management with automated data classification and lineage tracking.
- Design and enforce standardized data ingestion patterns with built-in quality controls and validation gates.
- Architect a centralized metrics repository that becomes the source of truth for all Leo metrics.
- Implement robust data quality frameworks with staging-first policies and automated validation pipelines.
- Design extensible metrics schemas that support complex analytical queries while optimizing for AI retrieval patterns.
- Develop intelligent orchestration for metrics generation workflows with comprehensive audit trails.
- Lead the design of semantic data models that balance analytical performance with AI retrieval requirements.
- Architect a globally distributed vector database infrastructure capable of managing billions of embeddings with consistent sub-100ms retrieval times.
- Design and implement hybrid search strategies combining dense vectors with sparse representations for optimal semantic retrieval.
- Establish automated compliance validation frameworks ensuring data handling meets Amazon's security standards.
About the team
The Amazon Global Selling Analytics, Intelligence, and Technology (AGS-AIT) team serves as the research, automation, and insight arm of the International Seller Service data hub, enabling rapid delivery of growth insights through strategic investments in regional data foundations, self-service business intelligence solutions, and artificial intelligence tools.
The AGS-AIT team is positioned to establish AI-ready foundational capabilities across the AGS organization while maintaining excellence in business insight generation, and self-service BI/AI application development.
AGS-AIT is looking for a Senior Data Engineer to collaborate with cross-functional teams to design and develop data infrastructure and analytics capabilities for AGS AI and Automation initiatives.
Basic Qualifications:
- 7+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience mentoring team members on best practices
- Experience communicating with users, other technical teams, and management to collect requirements, describe data modeling decisions and data engineering strategy
Preferred Qualifications:
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
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