Job Description

DESCRIPTION
Come build the future of smart security with us. Are you interested in helping shape the future of devices and services designed to keep people close to what's important?
About Ring
Since its founding in 2013, Ring has been on a mission to make neighborhoods safer. From the first-ever video doorbell, to the award-winning DIY Ring Alarm system, Ring's smart home security product line, as well as the Neighbors app, offer users affordable whole-home and neighborhood security. At Ring, we are committed to making home and neighborhood security accessible and effective for everyone -- while working hard to bring communities together. Ring is an Amazon company. For more information, visit www.ring.com. With Ring, you're always home.
Ring is looking for an insightful and analytical Business Intelligence Engineer with strong business and technical skills to join our Business Intelligence team. In this role, you will partner with product management, engineering, quality assurance and other BI teams that power Ring. Your work will be instrumental to achieving its mission, be highly visible to Ring / Amazon leadership, and will drive key strategic company goals.
The Business Intelligence Engineer, Ring Decision Sciences Platform BI team will develop models and tools, conduct statistical analyses, evaluate large data sets, and create tailored models and dashboards. Additionally, you will be instrumental in the creation of a reliable and scalable infrastructure for ongoing reporting and analytics. You will be structuring ambiguous problems and designing analytics across various disciplines, resulting in actionable recommendations ranging from strategic planning, product strategy/launches, and engineering improvements to marketing campaign optimization, customer servicing trending, and competitive research.
Key job responsibilities

• Enable decision-making by retrieving and aggregating data from multiple sources to present it in a digestible and actionable format
• Work with the ios and Android development and product teams to identify gaps and trends.
• Analyze large data sets using a variety of database query and visualization tools
• Provide technical expertise in extracting, integrating, and analyzing critical data
• Anticipate, identify, structure, and solve critical problems
• Design and develop key performance metrics and indicators using standardized and custom reports
• Perform ad hoc analysis to quickly solve time sensitive operational issues and business cases.
• Clearly communicate any potential data discrepancies and/or reporting downtime, including specific root cause, steps to resolution, and resolution date to a large end-user base
• Partner with subject matter experts to document and translate business requirements into technical requirements
• Manage multiple projects and proactively communicates issues, priorities, and objectives
• Clearly communicate any potential data discrepancies and/or reporting downtime, including specific root cause, steps to resolution, and resolution date to a large end-user base
• Partner with BI architects to provide valuable inputs to remodel the existing data warehouse.

A day in the life
As you lead the Business Intelligence Engineering (BIE) efforts for an upcoming device launch, your day involves collaborating closely with Product, Program, Firmware, and various other engineering teams. Having already identified the key signals to analyze device performance based on feature sets, you spend time aligning on proper definitions to analyze these features, meeting with engineering teams to instrument appropriate signals, maintaining data pipelines, and refining comprehensive dashboards. Throughout the day, you monitor platform performance while advancing initiatives to improve Ring's analytics through AI workflow implementation.
About the team
The Ring Decision Sciences Platform is responsible for the data strategy, architecture, governance, science, and software services Ring teams use to inform business strategy or power experiences with data. The central Data Science and Analytics team (within Decision Sciences and the team where this role is based) is responsible for core business metrics, shared data models, AI/ML models, business intelligence dashboards, and business analysis/science support.
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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