Distinguished Software Engineer, Data Infrastructure

Company Description

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

Job Description

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.

This role will be based in Mountain View, CA OR Bellevue, WA.

LinkedIn’s Data Infrastructure team builds and operates some of the largest online, offline and serving systems in the world. These systems are critical to our business success and we are constantly pushing the boundaries of scale, reliability and user experience.

We are seeking a Distinguished Engineer with deep expertise in Online Infrastructure, Platforms, and Databases to provide leadership across the Data Infrastructure organization. Online Data Infrastructure at LinkedIn delivers the specialized systems required to run LinkedIn’s user-facing, online applications with high availability, low latency, and optimal performance. Ranging across relational, document, caching, graph and serving systems this is a broadly scoped role with company level impact. This leader will leverage their broad infrastructure knowledge and work across online and offline data systems, other infrastructure and product teams to drive innovation, optimize performance, increase reliability and enable superior user experiences that increase customer engagement.

Responsibilities:

• Develop a comprehensive understanding of LinkedIn's infrastructure, particularly focusing on Online Infrastructure and Databases, and provide domain expertise and thought leadership.

• Lead and facilitate cross-functional technical discussions to align product and technology strategies, emphasizing developer productivity while meeting scale, performance, and efficiency requirements.

• Define and drive technical strategies and roadmaps that translate business requirements into robust architecture and technology plans.

• Design and architect highly scalable, resilient, and distributed systems to support Data Infrastructure objectives.

• Establish and advocate for best practices, design patterns, and quality standards for scalable Distributed Databases and caching systems.

• Identify and address gaps in the current infrastructure by recommending and implementing migration strategies for legacy systems.

• Mentor and guide senior engineering talent, fostering a culture of craftsmanship, innovation, and technical excellence.

• Represent LinkedIn as a thought leader by publishing technical papers, presenting at conferences, and driving industry innovation in Data Infrastructure.

• Collaborate with stakeholders to ensure the infrastructure supports LinkedIn's business goals and customer needs.

• Drive the adoption of new technologies and methodologies that enhance the performance, reliability, and maintainability of LinkedIn’s infrastructure.

• Ensure compliance with security and privacy standards, implementing measures to protect LinkedIn’s data and systems.

Qualifications

Basic Qualifications:

• Bachelor's degree in Computer Science or a related field, or equivalent experience

• 10+ years of experience in software engineering, with a focus on infrastructure, distributed systems, or databases.

Preferred Qualifications:

• Master's or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent research experience.

• Proven track record of technical leadership in building robust, scalable platforms

• Demonstrated expertise in designing, implementing, and managing large-scale, distributed systems that are both resilient and scalable.

• 5+ years of experience in a technical or scientific leadership position

• Proven ability to lead and mentor engineering teams, fostering a culture of technical excellence, innovation, and collaboration.

• Expertise in designing and implementing distributed databases, data and compute infrastructure at scale

• Experience identifying gaps in current infrastructure, recommending strategic improvements, and driving implementation of cutting-edge solutions to advance the field of Data Processing and Data Infrastructure

• Experience leading large-scale development projects from concept to production

• Proficiency with AI based development and the use of AI/ML in production systems

• Ability to drive cross-company initiatives and influence the evolution of infrastructure systems

• Excellent communication skills, with experience mentoring engineering talent and fostering a culture of collaboration and innovation.

Suggested Skills:

• Distributed Systems
• Online Infrastructure
• Databases

You will Benefit from our Culture
The pay range for this role is $253,000 to $416,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.


The total compensation package for this position may also include an annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit

Additional Information

Equal Opportunity Statement

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

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Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

• Documents in alternate formats or read aloud to you
• Having interviews in an accessible location
• Being accompanied by a service dog
• Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.

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Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

Pay Transparency Policy Statement ​

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Workplace Type: HybridCareer Track & Grade: IC7/12Department: Engineering