Business Intelligence Engineer, Alexa Endpoints

Alexa Mobile BI (AMBI) owns the analytics that measure the mobile success of Alexa+, the next generation of Alexa. As a Business Intelligence Engineer on this team, you will define what success looks like for a brand-new product still being shaped: how customers discover it, adopt it, engage with it day over day, and come back. Your work goes straight to the people making the calls. You will build the metrics, deep-dives, and dashboards that Product Managers and senior leadership use to set the mobile roadmap and make launch go/no-go decisions. An analysis you run this week can change what ships next month. We are also rebuilding how BI gets done. AMBI is investing in Generative and Agentic AI: AI agents that write SQL, automate recurring reporting, and stand up dashboards, plus natural-language, self-service analytics so PMs and leaders can answer their own questions instead of waiting in a queue. We want a builder who helps design these workflows, not just consume them. The ideal candidate is a self-starter with a strong bias for action, a communicator who can turn ambiguity into clear metrics, and an AI power user (or someone eager to become one) who uses modern tooling to raise the whole team's velocity. If you are excited by data, energized by a fast-moving launch, and want to own an analytics domain end-to-end with room to grow, this role is for you. Key job responsibilities * Own the metrics, datasets, and analytics for Alexa+ on mobile across adoption, entitlement, engagement, and retention, defining success measures for a product that is still being built. * Run deep-dive cohort and retention studies (retention curves, customer lifecycle stage, and lapse analysis) across voice, type, and tap engagement, plus feature-adoption studies that explain why the numbers move. * Build and maintain exec-facing business reviews and QuickSight dashboards that leadership relies on every week. * Partner directly with Product Managers and leadership to translate open questions into metrics, and to inform roadmap and launch (go/no-go) decisions. * Evaluate and interpret experimentation results. Measure the customer impact of A/B tests and feature experiments, and translate them into clear, evidence-based recommendations for launch and rollout decisions. * Help design and adopt agentic analytics workflows such as AI agents that generate SQL, automate reporting, and power natural-language self-service for stakeholders. * Build ETL and data models on the Data Lake/Warehouse (via Datanet/Cradle) and own data quality and metric consistency so every number tells the same, trusted story. A day in the life A PM pings you before the business review (BR): Alexa+ engagement dipped in one cohort. Is it real, or a reporting artifact? You pull the thread with a retention deep-dive, confirm it's a genuine early-lifecycle drop-off, and quantify it by modality. By mid-morning you've drafted the finding for the BR narrative and flagged it to the feature PM. In the afternoon you turn the one-off analysis into a reusable, self-service dashboard so the team can watch the cohort without asking you again, and you lean on the team's AI tooling to scaffold the SQL and the first pass of the build, so you spend your time on judgment, not boilerplate. You experiment, move fast, and keep learning.

Alexa Mobile BI (AMBI) is the analytics engine for the Alexa Mobile App. We measure engagement, retention, and the growth of Alexa+, and we are the source of truth for the WBR/MBR reporting that Product and leadership run the business on. We work across the full stack, from the Data Lake/Warehouse and Datanet/Cradle pipelines to QuickSight, and we are reinventing that stack with Generative and Agentic AI to move faster and go deeper than a traditional BI team. We move fast, experiment constantly, and balance strong technical craft with the business judgment to know which questions actually matter. This is a high-visibility product at a pivotal moment,