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Sr. Staff Software Engineer, Systems Infrastructure - Observability Streaming

LinkedIn
Bengaluru, IND
Full-time
Senior · 12+ years experience
Hybrid
Discovered Today
flinkjavakafkapythonspark

Full Job Posting

Basic Qualifications:

  • BA/BS Degree in Computer Science or related technical discipline, or equivalent practical experience
  • 12+ years of industry experience in software design and development, with problem-solving and system-design skills
  • 12+ years of experience programming in object-oriented languages such as Java, C++, Python, Go, C and/or other Functional languages
  • Experience building and operating large-scale streaming and real-time processing systems, including stateful processing and data delivery guarantees
  • Hands on experience developing large-scale observability platforms with a deep understanding of distributed systems, microservice architecture, Pub-Sub systems, logging /metrics / tracing platforms
  • 5+ years of experience in an architect or technical leadership position
  • 8+ years building and optimizing large-scale distributed processing systems and client-server architectures.
  • Experience with stream processing and messaging technologies such as Kafka, Flink, Samza, Beam, or Spark Streaming, including stateful stream processing, windowing, watermarks, and delivery semantics.
  • Depth in observability systems across metrics, logs, traces, and events, including high-cardinality ingestion and low-latency query at scale.
  • Experience building systems with AI and using AI-powered coding agents and assistants in everyday development to design, implement, test, and review software at a higher velocity and quality bar.
  • Ability to work with multiple stakeholders, understand product priorities, think big-picture, and solve core problems efficiently.
  • Excellent communication skills, with the ability to articulate complex technical concepts and drive technical strategy across teams and geographies.
  • Maintainer or contributor of open source projects
  • Technical Leadership
  • Distributed Systems (Streaming)
  • Real-Time Data Processing
  • Software Design
  • Cross-organizational Collaboration

Preferred Qualifications:

  • 8+ years building and optimizing large-scale distributed processing systems and client-server architectures.
  • Experience with stream processing and messaging technologies such as Kafka, Flink, Samza, Beam, or Spark Streaming, including stateful stream processing, windowing, watermarks, and delivery semantics.
  • Depth in observability systems across metrics, logs, traces, and events, including high-cardinality ingestion and low-latency query at scale.
  • Experience building systems with AI and using AI-powered coding agents and assistants in everyday development to design, implement, test, and review software at a higher velocity and quality bar.
  • Ability to work with multiple stakeholders, understand product priorities, think big-picture, and solve core problems efficiently.
  • Excellent communication skills, with the ability to articulate complex technical concepts and drive technical strategy across teams and geographies.
  • Maintainer or contributor of open source projects
  • Suggested Skills:
  • Technical Leadership
  • Distributed Systems (Streaming)
  • Real-Time Data Processing
  • Software Design
  • Cross-organizational Collaboration
  • You will Benefit from our Culture
  • We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
  • 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 https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
  • Global 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: https://legal.linkedin.com/candidate-portal.
  • Global Data Privacy Notice and Compliance Posters for Job Candidates
  • Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.
  • 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.

Responsibilities

  • Architect, build, run, and scale real-time streaming systems/real-time processing systems at massive scale.
  • Own the technical direction of the observability platform end to end - the collection, processing/enriching telemetry events and evolve it so insight keeps pace with the growth of our systems.
  • Scale distributed systems and make the hard architectural trade-offs - across processing models, data delivery guarantees, storage tiers, and the balance of cost, latency, and durability - while writing code and delivering with speed and quality.
  • Serve as a role model and coach for engineers, with a strong bias for action, providing architectural guidance and mentorship to up-level the engineering organization.
  • Develop multi-tier scalable, high-volume performing, and reliable user-centric applications that operate 24x7. Produce high-quality infrastructure that is thoroughly tested, code reviewed & resilient.
  • Partner with teams across the company to drive adoption of the platform(s), turning their instrumentation and diagnostic needs into measurable improvements in engineering productivity.
  • Work closely with leadership and product/technology partners to define the roadmap and surface opportunities to improve observability.
  • Navigate and resolve cross-team conflicts to align stakeholders and foster a cohesive, collaborative engineering culture.

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