Staff Network Engineer, Google Distributed Cloud

Google

Google is a leading technology company providing internet-related services and products.

San Francisco Bay Area, CA, USA

$168,000 - $252,000

Cloud

Staff Software Engineer

In-Person

5,000+ Employees

10+ years of experience

AI · Enterprise SaaS · Cloud

Description For Staff Network Engineer, Google Distributed Cloud

Google is proud to boast a network that provides service to millions of Internet users around the world. The Network Engineering team is responsible for operating that network reliably and at scale. As a member of the team, you have a direct impact on design and feature enhancements to keep our systems running smoothly. You also ensure that network operations are safe and efficient by monitoring network performance, coordinating planned maintenance, adjusting hardware components and responding to network connectivity issues. Google's complex network generates a constant stream of challenges which require you to continually be innovative with an evolving set of technologies. Keeping the network reliable ensures that our users stay connected with our suite of applications, products and services.

The Google Distributed Cloud Platform Network Engineering team consists of Network Engineers and architects designing the private network fabric using underlay and overlay network technologies that connects every GDC service together in air-gapped deployments. This involves collaboration with Network Automation Engineers and Network Engineers seeing their designs from start-to-finish, ensuring that designs arrive fully supported, validated, and observable. The team is composed of experts in physical and virtual networking that work in delivering network designs that connect private kubernetes clusters to the data center.

As a Staff Network Engineer for Google Distributed Cloud, you will be responsible for providing technical leadership, designing and implementing network solutions, and ensuring the stability and scalability of Google's distributed cloud infrastructure. You will work on complex network challenges, collaborate with cross-functional teams, and drive innovation in network technologies.

Key Responsibilities:

Lead projects to enhance network stability, scalability, and efficiency
Develop roadmaps and strategic plans for network improvements
Consult on service catalog options and provide feedback for future enhancements
Design and implement multi-vendor networks across various platforms
Drive engineering design and solution development for GDC infrastructure

Required Qualifications:

Bachelor's degree in Computer Science, Engineering, or related field
10+ years of experience in network routing protocols, design, and troubleshooting
Expertise in planning and designing complex networks
Proficiency in configuring data center and service provider network equipment

Preferred Qualifications:

Experience with programming languages like C++, Go, or Python
Knowledge of high-volume, high-availability network technologies
Familiarity with networking protocols (TCP/IP, BGP, EVPN, VXLAN, etc.)
Strong collaboration skills and ability to work in a global team environment

Join Google's Network Engineering team and help shape the future of distributed cloud infrastructure while ensuring reliable connectivity for millions of users worldwide.

Last updated 7 months ago

Responsibilities For Staff Network Engineer, Google Distributed Cloud

Provide technical leadership for projects to increase stability of the network, enhance scalability, efficiency and quality of network deployments
Produce analysis, efficiency and stability improvements, help in building roadmaps, scoping and planning at regional and global level
Assist the team in consulting with customer options available from the service catalog as well as provide feedback into Network, Engineering, Automation, and Operations organizations for future service enhancements
Ensure delivery of multi-vendor networks across various platforms and technologies, collaborate with other engineers and project managers to design, build, and turnover deployments to operations
Drive the engineering design, solution development, and functional/requirement analysis related to planning, design, installation, and implementation of GDC infrastructure

Requirements For Staff Network Engineer, Google Distributed Cloud

Python

Bachelor's degree in Computer Science, Engineering, a related field, or equivalent practical experience
10 years of experience with network routing protocols, design and troubleshooting, with network equipment providers
Experience with planning and designing networks (e.g., multiple sites, multiple products, etc.)
Experience in configuring data center and service provider routers, switches, and firewalls

Google

Google is a leading technology company providing internet-related services and products.

San Francisco Bay Area, CA, USA

$168,000 - $252,000

Cloud

Staff Software Engineer

In-Person

5,000+ Employees

10+ years of experience

AI · Enterprise SaaS · Cloud

Google

How would you implement a placement system for cars in a racing game with a circular track?

Data Structures & AlgorithmsHard

Imagine you are developing a racing game. You need to implement a system that determines the placement of each car in the race at any given moment. The race track is a circular track of a fixed length. Each car has a unique ID and a current distance traveled from the starting line. Design a function that takes a list of cars, where each car is represented by its ID and distance traveled, and returns the current placement of each car, considering the circular nature of the track. For example, if the track length is 1000 meters and a car has traveled 1200 meters, its actual position on the track is 200 meters. Consider edge cases such as multiple cars having the same position. Can you implement a function that efficiently calculates and assigns placements to the cars based on their positions on the track?

Arrays

Greedy Algorithms

Google

Design a scalable and accurate rate limiter.

System DesignMedium

Let's design a rate limiter. This is a crucial component in many systems to prevent abuse and ensure fair usage. Your rate limiter should meet these requirements: Functionality: It should limit the number of requests a user can make within a specific time window. For example, allow a user to make 10 requests per minute. Scalability: The rate limiter needs to handle a large number of users and requests concurrently. Imagine millions of users accessing the system. Accuracy: It should accurately track and enforce the rate limits. A small degree of error is acceptable, but significant deviations are not. Low Latency: The rate limiter must not introduce significant delays in request processing. The overhead should be minimal. Fault Tolerance: The system should continue to function correctly even if some components fail. It should be resilient to outages. Cost-Effectiveness: The solution should be cost-effective in terms of resources used (e.g., memory, CPU, network bandwidth). Consider these scenarios and constraints: Users are identified by a unique ID. The time window is configurable (e.g., seconds, minutes, hours). The rate limit is also configurable per user or group of users. You can use any data structures and algorithms you deem appropriate. Assume you have access to a distributed cache (e.g., Redis, Memcached). Walk me through your design. Discuss different approaches, their trade-offs, and how you would address the requirements. Specifically, consider the following: Data structures for storing request counts. Algorithms for incrementing and checking request counts. Handling concurrency and race conditions. Strategies for distributing the rate limiter across multiple servers. How to handle exceeding the rate limit (e.g., returning an error code). Monitoring and alerting. For example, if a user with ID user123 tries to make 11 requests within a minute when their limit is 10, the rate limiter should reject the 11th request. How would your system achieve this efficiently and reliably at scale?

Arrays

Strings

Two Pointers

Stacks

Binary Search

Sliding Windows

Linked Lists

Trees

Recursion

Graphs

Dynamic Programming

Greedy Algorithms

Bit Manipulation

Database Problems

Google

Where do you see yourself in 5 years?

Behavioral

Where do you see yourself in 5 years?

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