Want to define how millions of customers experience third-party services through Alexa+? Alexa 3P Quality & Experiences ensures every ride booking, restaurant reservation, and travel plan delivers a frictionless experience. If you're passionate about turning raw customer signals into actionable quality insights—while operating at the intersection of Generative AI and large-scale data systems—this role is for you. Work with us to scale quality for 3P experiences across multiple integration patterns and international locales, all while pioneering AI-powered quality improvements and fixes.
The Alexa 3P Quality & Experiences team is seeking an experienced Business Intelligence Engineer who transforms ambiguous, high-volume customer experience data into metrics that drive decisions. Using a combination of deep technical skills and cross-functional influence, this candidate will be the key BI partner between quality monitoring operations, ASK product teams, and 3P partner engagement. Primary areas of focus will be: 1) defining and operationalizing quality metrics (CPDR, CPQR, friction rates, task completion funnels) across experiences and locales, 2) building scalable data pipelines that power AI-driven investigation tools, and 3) deep-diving large datasets to surface cross-expert defect patterns invisible to manual analysis.
A successful candidate will be an expert with SQL, ETL, and data modeling for customer experience signals at scale. They will build dashboards that translate high-volume utterance data into clear quality narratives for VP-level reviews. The candidate will need to be a self-starter, comfortable with ambiguity in a fast-paced environment with rapidly expanding scope, and able to think big about automation-first measurement systems while paying careful attention to data accuracy and statistical rigor.
Key job responsibilities
- Interface directly with stakeholders, gathering requirements and owning automated end-to-end reporting solutions.
- Develop complex queries for ad hoc requests and projects, as well as ongoing reporting.
- Design, develop and maintain scalable, automated, user-friendly systems, reports, dashboards, etc. that will support our analytical and business needs
- Design, implement, and support key datasets that provide structured and timely access to actionable business information addressing stakeholder needs.
- Proficiency with SQL queries to retrieve and analyze data. Learn and understand a broad range of Amazon’s data resources and know how, when, and which to use.
- Perform end-to-end deep dive analyses to discover actionable insights for our business stakeholders.
- Simplify and automate reporting, audits, and other data-driven activities; build solutions to have maximum scale and self-service ability by stakeholders
- Apply engineering excellence to reporting and analysis pipelines, automate and simplify self-service support for customers.
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
A day in the life Your primary focus is turning messy, high-volume customer experience data into the metrics and dashboards that tell leadership what's broken, why, and what to fix first—across both pre-launch quality assurance and post-launch monitoring for third-party experiences on Alexa+.
On a typical day, you'll pull overnight quality signals, validate whether a metric spike is a real customer problem or a data artifact, and have an answer ready before standup. You'll build and maintain the data pipelines that feed AI-powered investigation tools—and then audit those tools to prove they're actually accurate. You'll partner with product engineers to quantify defect impact, with operations teams who use your dashboards to prioritize investigations, and with partner-facing teams who need data to drive conversations with third-party developers. You'll also work closely with AI/ML tool owners—providing ground-truth datasets and measuring whether automation is delivering on its promise.
Beyond the day-to-day, you'll shape how quality is measured as new experiences and international markets launch. You'll define what "good" looks like before Day 1, build the scorecards that track it, and own the narrative in weekly executive reviews.
About the team The Alexa Enterprise (AE) mission is to extend Alexa's capabilities and services to partners, accelerating Alexa's vision of creating the smartest, most capable and trusted AI personal assistant. We help our partners create value, and deliver a business we love. Our business mission is focused towards the following areas:
- Distribute Alexa across 3P endpoints such as smart TVs and speaker profitably drive incremental endpoints and new-to-Alexa customer acquisition
- Bring value to customers in hotels, senior living communities, and healthcare properties
- Offer branded conversational AI assistants to partners
- Ensure product certification, quality checks, and developer support to partners We serve world-class customers across the industry. Our products have been featured in publications such as CNET and Forbes, and Amazon has celebrated our progress in its quarterly earnings highlights. Our vision is for Alexa to become an integral part of our enterprise customers, driving revenue, lowering costs, and improving end user satisfaction. Our team values work-life harmony and a diversity of lifestyles and family schedules
Basic Qualifications
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
Preferred Qualifications
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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