Business Intelligence Engineer, Alexa Enterprise Data

Want to transform the way people experience Alexa on Enterprise? Then come join the team that delivers the global experience on Alexa Enterprise. If you’re passionate about building magical experiences for customers, while solving hard, complex technical problems, then this role is for you. Work with us to deliver industry leading experiences across a growing array of Alexa supported devices and countries, all while being at the forefront of Generative AI and LLM capabilities
The Alexa Enterprise Data org is seeking an experienced Business Intelligence Engineer who is a master of both data insights and relationship-building. Using a special combination of technical and people skills, this candidate will be the key BI liaison between Alexa audio feature owners and other partner teams. Primary areas of focus will be 1) defining metrics and KPIs, and 2) deep-diving ambiguous and large data sets.

A successful candidate will be an expert with SQL, ETL (and general data wrangling) and have exemplary communication skills. The candidate will need to be a self-starter, comfortable with ambiguity in a fast-paced and ever-changing environment, and able to think big while paying careful attention to detail.

Key job responsibilities
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
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

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:
1) Distribute Alexa across 3P endpoints such as smart TVs and speaker profitably drive incremental endpoints and new-to-Alexa customer acquisition
2) Bring value to customers in hotels, senior living communities, and healthcare properties
3) Offer branded conversational AI assistants to partners
4) 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- 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- 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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