Amazon
Business Intelligence Engineer, Amazon Customer Service
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Business Intelligence Engineer, Amazon Customer Service
Business Intelligence Engineer – Data Analytics Support Hub
Amazon's Customer Service organization is seeking a Business Intelligence Engineer to join the Data Analytics Support Hub. Customer Service is the heart of Amazon. Our vision is to be Earth's most customer-centric company, and this team plays a central role in understanding why customers need to contact us and how we can prevent those contacts from happening in the first place.
The Advanced Analytics team is evolving Quality and Escalations analytics from descriptive reporting ("what happened") to diagnostic ("why did it happen") analytics at a worldwide level. We build the data infrastructure that powers:
- Multi-contact journey analysis,
- Large-scale transcript processing,
- Machine-learning-driven root-cause identification across billions of customer interactions.
Key Responsibilities
In this role, you will:
- Design and own the production data pipelines that turn domain expertise into scalable diagnostic insights.
- Work across the full data lifecycle, from ingestion and modeling through certification and serving.
- Enable stakeholders to self-serve answers to complex "why" questions without waiting for ad-hoc analysis.
- Directly feed Weekly Business Reviews, leadership dive-deeps, and the automation of diagnostic narratives using large language models (LLMs).
This is an opportunity to combine deep data engineering craft with high-visibility business impact. You will operate at the intersection of large-scale data infrastructure and applied AI, shipping systems that meaningfully improve how Amazon understands and acts on customer experience signals worldwide.
Core Accountabilities
- Build and own:
- Production data pipelines for diagnostic workloads, including:
- Transcript ingestion at worldwide scale,
- Multi-contact threading,
- Journey-grain feature tables,
- Model-serving datasets.
- Production data pipelines for diagnostic workloads, including:
- Design and maintain: End-to-end data models for the team’s KPI portfolio, from raw source integration through consumption-ready tables.
- Integrate team pipelines with central Customer Service data infrastructure, consuming shared tooling and contributing reusable components.
- Scale innovations from analyst prototypes into maintainable, certified production pipelines with appropriate monitoring and alerting.
- Build and maintain the transcript prototyping infrastructure used by stakeholders for self-service, reducing time-to-delivery for new analytical requests.
- Productionize LLM-based diagnostic outputs into reliable, refreshable datasets that power automated "why" narratives and self-service dive-deeps.
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About the Team
The Data Analytics Support Hub is a high-impact group responsible for diagnostic analytics across Amazon Customer Service worldwide. We answer the "why" behind quality and experience trends.
Our team combines:
- Business analytics,
- Data engineering,
- Data science,
- Business intelligence expertise.
We operate across the full stack:
- From raw transcript ingestion pipelines,
- Through feature engineering,
- LLM-based classification,
- To executive-facing automated narratives.
We partner closely with operations, science, and product teams across CS to translate complex multi-interaction journey data into actionable insights that drive real improvements for customers.
Basic Qualifications
- Experience in analyzing and interpreting data with:
- Redshift,
- Oracle,
- NoSQL platforms.
- Experience with data visualization using:
- Tableau,
- QuickSight, or similar tools.
- Experience with:
- Data modeling,
- Warehousing,
- Building ETL pipelines.
- Experience in statistical analysis packages such as:
- R,
- SAS,
- Matlab.
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling.
- Experience with AWS solutions including:
- EC2,
- DynamoDB,
- S3,
- Redshift.
- Experience in:
- Data mining,
- ETL, ect.
- Experience using databases in a business environment with large-scale, complex datasets.
- Master’s degree in:
- BI,
- Finance,
- Engineering,
- Statistics,
- Computer Science,
- Mathematics, or an equivalent quantitative field.
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Preferred Qualifications
- Experience productionizing LLM-based diagnostic outputs into reliable datasets.
Amazon’s Commitments & Requirements
-
Equal opportunities employer: We do not discriminate on the basis of protected veteran status, disability, or other legally protected status.
-
Diversity & inclusion:
- Employing a diverse workforce is central to our success.
- Recruiting decisions are based on experience and skills.
- Valuing your passion to discover, invent, simplify and build.
-
Privacy processes:
- Protecting your privacy and data security is a priority. For details, see our Privacy Notice.
Accommodations: If you have a disability and need workplace accommodations, please visit Accommodations. If the country/region isn’t listed, contact your Recruiting Partner.
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