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.

　　At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together.

　　We are seeking a Senior leader to lead our rock star team responsible for developing and operating LinkedIn's platform that is responsible for our Data Processing Platforms (stream and Batch), Data Analytics platform, Data Lake, Data Pipelines, Change Capture and data ingestion pipelines, Orchestration frameworks for data processing and machine learning and the overall big data ecosystem . As a key player in our mission-driven organization, you will contribute to the vision of creating economic opportunities by ensuring the scalability, reliability, and efficiency of all our data systems. LinkedIn is a Data company and all of LinkedIn’s applications are built on top of the features and capabilities provided by this team.

　　Responsibilities:

　　The leader of this team is responsible for operating the largest scale systems at LinkedIn. The leader also has to partner with a very wide variety of other teams that are responsible for compliance, data management tools, low level compute infra, machine learning, data scientists etc.

　　Lead, motivate and challenge the most senior infrastructure engineering team at LinkedIn. -

　　Lead new initiatives to scale our platform and also dramatically increase developer productivity for all LinkedIn application developers by offering best in class Batch and Stream processing platforms. This includes initiatives to build a converged data processing offering where applications can be built using SQL, Java, Python once but get run in either near real time (stream processing) or batch environments while making it trivial to move state and data between them.

　　Lead the teams responsible for Orchestrator offerings that allow for traditional data processing flows, machine learning flows and operational flows.

　　Managing the multi-exabyte DataLake for all of LinkedIn and ensuring that it is compliant, easy to access and scalable.

　　Data Pipelines that bring the data into the DataLake and also move data between various sources and sinks. This includes Change Capture system that allows for changes in our Databases to be processed in near real time or offline.

　　Analytics platform that is used for all data exploration at LinkedIn by Data Scientists and LinkedIn engineers

　　Work on building and enhancing governance strategies, particularly in terms of security and cost control, aligning with LinkedIn's commitment to providing a secure and reliable platform.

　　Be responsible for the availability, scalability for the Big Data Ecosystem of Services at LinkedIn.

　　Be responsible for upleveling the developer experience and productivity for all LinkedIn engineers that operate on data.

　　Partner closely with other infrastructure teams like Machine learning infra, compute infrastructure, data compliance and management, Data scientists etc.

　　As a senior leader in Data Infrastructure at LinkedIn, influence and push the technology stack across all Data systems.

　　Basic Qualifications:

　　Master's degree or higher in Computer Science, Engineering, or a related field.

　　10+ years of relevant work experience.

　　Background in designing and operating large-scale data infrastructure systems.

　　Deep experience in building open-source technologies and a commitment to contributing to the community.

　　Proven skills in leading large software infrastructure systems and services.

　　Building and operating very high scale distributed systems

　　Communication skills - clarity of thought and clarity of speech.

　　Leadership - Ability to make hard decisions while bringing people together and ensure the team works towards clear goals and achieves the business goals.

　　Preferred Qualifications

　　PhD in Computer Science

　　12+ years' experience in large-scale data infrastructure and distributed systems.

　　Suggested Skills:

　　Leadership

　　Experience building large scale systems

　　Executive communication

　　LinkedIn is committed to fair and equitable compensation practices.

　　The pay range for this role is $229,000 to $375,000. 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 https://careers.linkedin.com/benefits.

　　Equal Opportunity Statement

　　LinkedIn is committed to diversity in its workforce and is 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 an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: https://microsoft.sharepoint.com/:b:/t/LinkedInGCI/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1C_QxVTbg?e=5hfhpE. Please reference https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf for more information.

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