RDSE Software Support Engineer, Ring

- 2+ years of software development, or 2+ years of technical support experience
- Bachelor's degree in engineering or equivalent
- Experience troubleshooting and debugging technical systems
- Experience in Unix
- Experience scripting in modern program languages
- Good knowledge about Database concepts
- Experience with AWS, networks and operating systems
RING, part of Amazon, focuses on smart home security products, primarily known for its video doorbells and security cameras. The RING system allows users to monitor their homes in real-time through video feeds, receive motion alerts, and communicate with visitors via two-way audio. RING's ecosystem integrates with various smart home devices, enhancing overall security and convenience. It also includes a community aspect, where users can share and access local security information through the Neighbors app.

The Ring Data Science and Engineering team owns products and services for Ring's growing analytics and operational needs. The portfolio of services managed by the team allow centralized data collection, aggregation and the building of standardized data models for analytics use cases.

Our mission is to accelerate innovation and promote data driven decision making across every aspect of Ring's business. To accomplish this mission we build products and services that streamline data collection, deliver a set of standard, unambiguous metrics and analytics tools, identify opportunities to deploy machine learning and deliver actionable insights and provide tools that enable privacy by design for all of Ring's products and services.

Key job responsibilities
• Provide support for technical and operational tasks for Ring Data Science Engineering Team.
• Provide support of incoming tickets, including extensive troubleshooting tasks, with responsibilities covering multiple products, features and services
• Work on operations and maintenance driven coding projects and AWS technologies
• Software deployment support in staging and production environments
• Automate processes to reduce operations and maintenance
• System and Support status reporting
• Ownership of one or more Digital products or components
• Customer notification and workflow coordination and follow-up to maintain service level agreements

About the team
Ring Data Science and Engineering is organized into three sub-organizations: 1) Data Operations, 2) Data Warehouse, and 3) Data Science and Analytics. Originally established to drive Ring's data strategy, governance, architecture, analytics platforms, and business insights, we are now expanding our focus to support Blink, Key, and Sidewalk.
Data Operations is responsible for large-scale data collection services (e.g., API services), near-real-time telemetry streaming (e.g., Kinesis/Kafka), and operational analytics platforms (e.g., Splunk). This organization is divided into four teams: EventStream, LogStream, Quick Action Service (QAS), and Database Engineering.
Data Warehouse handles foundational data engineering pipelines (e.g., Airflow jobs using EMR), analytics platforms (e.g., Athena, Redshift, Tableau), and privacy compliance automation services (e.g., API services). This org is also divided into four teams: Platforms, Business Vertical Data Pipelines, Data Quality, and Data Privacy. These two-pizza teams primarily consist of Data Engineers, Software Development Engineers, and System Development Engineers.
Data Science and Analytics is responsible for Ring’s foundational AI/ML models, core business metrics, shared data models, product analytics dashboards, and analyst/scientist support. This organization is split into two teams: Business Intelligence and Data Science, with team members primarily comprising Business Intelligence Engineers and Data Scientists.