Senior Data Engineer, Amazon Customer Service
About The Position
This role is on the Amazon Defect Elimination Analytics team, which aims to create a defect-free customer experience by developing technology that quickly identifies defects, links them to root cause information, and prioritizes improvement opportunities based on business and customer needs. The Senior Data Engineer will collaborate with Software Developers, Research Scientists, Business Intelligence Engineers, and Program & Product Managers to provide insights on customer feedback, establish key performance indicators for products, and support feature engineering and model development. A significant part of the role involves building the data infrastructure for AI/ML and LLM-based systems, including designing pipelines for agentic workflows and retrieval-augmented generation (RAG) architectures. The ideal candidate possesses strong business acumen, organizational skills, resilience, experience in measuring product performance, and the ability to collaborate effectively with product owners to address critical questions. The work environment is fast-paced and dynamic, with a strong team-oriented and welcoming culture. Success in this role requires attention to detail, enthusiasm, and flexibility, offering significant experience with cutting-edge big data technologies, generative AI infrastructure, and exposure to statistical and Natural Language modeling through collaboration with scientists on global issue detection models.
Requirements
- 5+ 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 with AI/ML technologies
Nice To Haves
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
Responsibilities
- Design, develop and maintain scaled, automated, user-friendly systems, reports, dashboards, etc.
- Partner with operations/business teams/economist/ML teams to consult, develop and implement KPI's, automated reporting/process solutions and data infrastructure improvements to meet business needs.
- Build and maintain data infrastructure for AI agent systems, including vector databases, embedding pipelines, and retrieval-augmented generation (RAG) data stores.
- Design data architectures that enable agentic workflows - structured data access layers, tool-use APIs, context management systems that AI agents consume autonomously, self-serve analytics.
- Develop observability and evaluation pipelines for LLM-powered features, including tracking model performance, hallucination rates, latency, and cost metrics at scale.
- Apply analytic skill to extract meaningful insights and learnings from large and complicated data sets, including unstructured text corpora used for generative AI applications.
- Serve as liaison with Business and technical teams to achieve project objectives, requiring data gathering, problem solving, modeling, and communication of insights and recommendations.
- Stay current with advances in AI/ML data infrastructure (e.g., feature stores, vector search, streaming inference pipelines) and evaluate their applicability to defect elimination use cases.
Benefits
- health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
- 401(k) matching
- paid time off
- parental leave
- sign-on payments
- restricted stock units (RSUs)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
