Business Intelligence Engineer, Comms Experience Insights

The vision for Alexa is to be the world’s best personal assistant. Such an assistant will play a vital role in managing the communication lives of customers, from drafting communications to coordinating with people on behalf of customers. At Alexa Communications, we’re leveraging Generative AI to bring this assistant to life.

If you’re passionate about building magical experiences for customers, while solving hard, complex technical problems, then this role is for you. You will operate at the intersection of large language models, real time communications, voice and graphical user interfaces, and mixed reality, to deliver cutting edge features for end customers.

Come join us to invent the future of how millions of customers will communicate with and through their virtual AI assistants.



Key job responsibilities
The Comms Experience Insights (CXI) Business Intelligence team is looking for an experienced, self-driven, analytical, and strategic Business Intelligence Engineer. We are looking for an individual who is passionate about tying together huge amounts of data to answer complex stakeholder questions. You should have deep expertise in creation and management of datasets and the proven ability to translate the data into meaningful insights through collaboration with Data Engineers (DEs) and Business Analysts (BAs). You should also have extensive experience in metric creation and explaining how those metrics impact a business. In this role, you will have ownership of end-to-end development of business intelligence solutions and you’ll play an integral role in strategic decision-making.

The right candidate will possess excellent business and communication skills, be able to work with business owners to develop and define key business questions and be able to collaborate with DEs and BAs to analyze data that will answer those questions. You should have a solid understanding of how to build efficient and scalable reporting solutions, dashboards and data models, and the desire to learn and implement new technologies and services to further a scalable, self-service model.

A day in the life
When we work together, we:

- Centralize the sprint and consolidate to one queue but still give stakeholder visibility and continue to ask feedback;
- Advocate knowledge sharing and code review;
- Avoid single point of failure with a secondary owner as code reviewer, mentor, backup, etc;
- Consolidate across org initiatives to the same primary owner;
- Train everyone on the must-have knowledges;
- Carve out time for high-sev tt, urgent requests, tech debt failure;
- Favor problem statement other than data requests