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 Bangalore India.
As part of our world-class Infrastructure engineering team at LinkedIn you will lead the Reliability Infrastructure charter to build next-generation reliability platforms and systemic resilience solutions that safeguard LinkedIns most critical Online Data and Streaming Services. Partnering with some of the best engineers in the industry you will apply your expertise in distributed systems and operational excellence to strengthen the foundations that power our member and revenue experiences. Leveraging deep expertise in OLTP databases such as MySQL streaming systems such as Kafka and compute infrastructure powered by Kubernetes you will design automation-first systems strengthen observability enable intelligent autoscaling and self-healing mechanisms and proactively chaos test our platforms to protect SLAs at global this role you will drive meaningful reductions in time to detect and mitigate incidents while accelerating AI-native engineering practices that transform how reliability is built and operated at LinkedIn creating durable company-wide impact across our data and streaming backbone. LinkedIn has pioneered widely adopted open-source infrastructure projects such as Apache Kafka Pinot Azkaban Samza Venice DataHub and Feather and we continue to build on industry-standard technologies like Kubernetes gRPC and GraphQL. Join us to advance the state of large-scale infrastructure while making real impact across the company and the broader engineering community.
Responsibilities:
- Manage the performance and career development of a team of engineers and own significant parts of LinkedIn products that require design architecture and coding.
- Participate with senior management in developing a long-term technology roadmap.
- Be a role model and professional coach for engineers with a strong bias for action and focus on craftsmanship.
- Work with peers across teams to support and leverage a shared technical stack.
- Manage teams to scale distributed applications make architectural trade-offs applying synchronous and asynchronous design patterns review code and deliver with speediness and quality.
- Develop multi-tier scalable high-volume performing and reliable user-centric applications that operate 24x7.
- Produce high-quality software that is unit tested code reviewed and checked in regularly for continuous integration.
Qualifications :
Basic Qualifications:
BA/BS Degree in Computer Science or related technical discipline or equivalent practical experience.
14 years of industry experience in software design development and large-scale software engineering
3 years of experience in software engineering/technical management and people management.
Experience programming in object-oriented and/or functional programming languages(like Java/CPP/Scala/etc.)
Hands on experience developing distributed systems databases large scale data systems and/or Backend APIs
Experience with OLTP databases (e.g. MySQL Postgres Oracle) Streaming services (e.g. Kafka Northguard Spark) Big Data Distributed systems. Should be able to leverage AI first practices for all the aspects of SDLC.
Preferred Qualifications:
- MS or PhD in Computer Science or related technical discipline
- 4 years of software engineering management experience
- 2 years experience managing managers
Suggested Skills:
- Technical Leadership
- People Management
- Stakeholder Management
Additional Information :
India Disability Policy
LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers including individuals with disabilities. For more information on our equal opportunity policy please visit Data Privacy Notice for Job Candidates
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: Work :
No
Employment Type :
Full-time
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