Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
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, with a vision to be Earth's most customer-centric company. This team plays a central role in understanding why customers contact us and how to prevent those contacts from happening. The Advanced Analytics team is evolving Quality and Escalations analytics from descriptive reporting ("what happened") to diagnostic analytics ("why did it happen") at a global scale. You will design and own production data pipelines that transform domain expertise into scalable diagnostic insights, working across the full data lifecycle from ingestion and modeling through certification and serving. Your work will enable stakeholders to self-serve answers to complex "why" questions without waiting for ad-hoc analysis, directly supporting Weekly Business Reviews, leadership deep-dives, and automation of diagnostic narratives using large language models. This role combines deep data engineering skills with high-visibility business impact, operating at the intersection of large-scale data infrastructure and applied AI to improve how Amazon understands and acts on customer experience signals worldwide.

Key Responsibilities
- Build and own production data pipelines for diagnostic workloads including transcript ingestion at worldwide scale, multi-contact threading, journey-grain feature tables, and model-serving datasets
- 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 transcript prototyping infrastructure used by stakeholders to self-serve, reducing time-to-delivery for new analytical requests
- Productionize LLM-based diagnostic outputs into reliable, refreshable datasets powering automated "why" narratives and self-service deep-dives

About the Team
The Data Analytics Support Hub is a high-impact group responsible for diagnostic analytics across Amazon Customer Service worldwide. The team combines business analyst, data engineering, data science, and business intelligence expertise, operating across the full stack from raw transcript ingestion pipelines through feature engineering, LLM-based classification, and executive-facing automated narratives. The team partners closely with operations, science, and product teams to translate complex multi-interaction journey data into actionable insights that drive real improvements for customers.

Experience
- Analyzing and interpreting data with Redshift, Oracle, NoSQL or similar
- Data visualization using Tableau, Quicksight, or similar tools
- Data modeling, warehousing, and building ETL pipelines
- Statistical analysis using packages such as R, SAS, or Matlab
- Using SQL for data extraction and Python scripting for data processing
- Experience with AWS solutions including EC2, DynamoDB, S3, and Redshift
- Data mining and working with large-scale, complex datasets in a business environment

About You
Detail-oriented and passionate about transforming data into actionable insights. Comfortable working at the intersection of data engineering and applied AI. Collaborative team player who thrives in a fast-paced, high-impact environment. Strong communication skills to partner effectively with cross-functional teams.

Qualifications
Master's degree in Business Intelligence, Finance, Engineering, Statistics, Computer Science, Mathematics, or an equivalent quantitative field preferred.