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Description

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

Come innovate with the Ring Team!

As a Support Engineering Manager, you will lead a diverse team of Support and Data Engineers in delivering technical support for externally-facing services while driving operational excellence and enhancing customer experiences. You will shape your team’s strategic direction by establishing clear performance metrics and aligning them with organizational goals. Your focus on senior engineer growth will create opportunities for leadership development and foster a culture of continuous improvement. By simplifying processes, optimizing team performance, and effectively communicating across functions, you will ensure high-quality solutions and maintain a psychologically safe environment that encourages innovation and collaboration. Your leadership will also influence cross-functional initiatives and drive impactful discussions to balance proactive and reactive customer support.

• Lead a team in undefined problem areas, engaging stakeholders and defining long-term strategies based on customer needs.

• Manage teams, including ICs and other managers, and recruit top talent.

• Establish metrics for progress, operational excellence, and support goals.

• Create onboarding plans, delegate responsibilities, and conduct performance evaluations to foster an inclusive team culture.

• Monitor and resolve trouble tickets within SLAs, drive the team to perform root cause analysis and providing deployment support.

• Drive the team to develop automated frameworks and tools for monitoring business outcomes while nurturing talent in application development.

• Collaborate with internal business owners to understand requirements and drive improvements.

• Drive initiatives to maximize operational efficiency and optimize processes.

• Communicate clearly with leadership, present decisions, and mentor team members to enhance performance.

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.

Basic Qualifications

• BS in Computer Science/Engineering or equivalent industry experience

• Robust understanding of support engineering processes

• 5+ years of experience in managing the larger support organization

• 12+ years of total experience, including a strong background as an individual contributor in a production support environment

Preferred Qualifications

• Experience hiring, mentoring, developing, and managing highly-successful and efficient product support and data engineering teams

• Have been successful working across organizational boundaries, bringing together people with diverse perspectives and experience to find solutions

• Experience working in Linux environments

• Strong desire to build, sense of ownership, urgency, and drive

• Understanding of big data technologies such as Hadoop, Hive, Spark, EMR

• Knowledge of any ETL tools like Informatica, ODI, SSIS, BODI, Datastage, etc.

• Knowledge of distributed systems as it pertains to data storage and computing

• Experience in administering reporting/analytics platforms

• Experience with SQL

• Experience with one or more scripting language (e.g., Python, Shell)

• Experience in Troubleshooting the issues related to Production Support, Data and Infrastructure issues.