Sr. Staff Software Engineer, Systems Infrastructure

LinkedIn•Mountain View, CA

6d•Hybrid

About The Position

This role will be based in Mountain View, CA. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. The Streams Infrastructure team at LinkedIn builds and operates highly scalable and available pub-sub, stream processing and data pipeline services for all of LinkedIn’s data platforms and applications. Kafka, Samza and Brooklin all originated at LinkedIn and form the backbone of the streaming infrastructure. More than 20+ trillion messages/day are ingested into the Kafka clusters from tracking site engagement to metrics and logging, while over 4+ trillion messages/day are processed by Samza for real-time data analytics that powers member notifications, threat screening, ads infrastructure etc. Data pipelines which include Brooklin moves over 6+ trillion messages/day and powers tens of thousands of data streams including Kafka mirroring. With tremendous scale comes unique scale and operability challenges. Because we host one of the largest scale streaming systems in the industry, we work on these challenges to ensure no data loss, multi-tenancy with strong failure isolation, and balanced work distribution / coordination, all while maintaining low latency delivery of events. As a Sr. Staff Software Engineer, you will be a key technical leader and role model within the organization. We are looking for a technical lead who designs and develops technology to serve business and technology objectives, aligns points of view across teams and makes trade offs to help achieve the goals of individual teams as well as LinkedIn's broader goals. You will foster LinkedIn's culture and values around transformation, collaboration and results. You will work closely with technical leadership and management within and outside our organization to contribute to building best-in-class core systems infrastructure for LinkedIn.

Requirements

BS/BA in Computer Science or related technical field or equivalent technical experience
5+ years of industry experience in software design, development, and algorithm related solutions
5+ years of experience programming in object-oriented languages such as C/C++, Java, Go, Rust, Python, Scala
2+ years of experience as an architect, or technical leadership position
Hands-on experience developing large-scale, distributed systems, and databases

Nice To Haves

MS or PhD degree in Computer Science or related technical discipline
10+ years of experience in software design, development, and algorithm related solutions with at least 5 years of experience in a technical leadership position
10+ years of experience in an object-oriented programming language such as C/C++, Java, Go, Rust, Python, Scala
5+ years of experience with large-scale distributed systems and client-server architectures
Experience in architecting and designing large-scale distributed systems related to data infrastructure, IaaS, ML/AI infrastructure, storage, graph, Kubernetes, and platforms.

Responsibilities

You will build and ship software, drive architectural decisions and implementation across the Stream Processing infrastructure at Linkedin (Apache Kafka, Northguard, Apache Flink, and other new initiatives)
You will actively improve the level of craftsmanship at LinkedIn by developing best practices and defining best strategies.
You will lead cross team/cross functional discussions and drive alignment on product/technology strategy.
You will define the bar for quality and efficiency of software systems while balancing business impact, operational impact and cost benefits of design and architectural choices.
You will act as one of the primary domain experts to influence technology choices.
You will lead by example to build a culture of craftsmanship and innovation.
You will act as someone who uses AI to solve problems, improves productivity and uplifts the team to do so.