Senior Staff Data Platform Software Engineer (Java, Kafka, Kubernetes)

Overview

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

The Data Platform group builds highly scalable, high‑performance platform capabilities for data‑in‑motion and backend storage systems. Our customers operate at massive scale, pushing the boundaries of data volume, throughput, and concurrency. We are looking for a seasoned IC5 Senior Staff Engineer with deep expertise in distributed systems, data ingestion pipelines, and Data Lake architectures to drive next‑generation platform innovation.

Role Summary: As an IC5 Senior Staff Engineer, you will architect and deliver large‑scale distributed platform components, lead complex technical initiatives, and define engineering best practices. You will bring strong leadership, hands-on engineering depth, and the ability to design and operate reliable, scalable, and high‑performance data systems.

Key Responsibilities

• Architect, design, and build high‑performance distributed systems and platform components.
• Build distributed systems data ingestion solutions with strong emphasis on scalability, quality, and operational excellence.
• Design software that is easy to use, extend, and customize for customer‑specific environments.
• Deliver high‑quality, clean, modular, and reusable code while enforcing engineering best practices (code reviews, unit testing, automation, design reviews).
• Build foundational libraries, frameworks, and tools focused on modularity, extensibility, configurability, and maintainability.
• Collaborate across engineering teams to refine requirements and deliver end‑to‑end solutions.
• Provide technical leadership for projects with significant complexity and risk.
• Research, evaluate, and adopt new technologies that enhance platform capabilities.
• Troubleshoot and diagnose complex production issues across distributed systems.
  
  

• 15 to 20 years of hands‑on engineering experience in distributed systems, data platforms, or large‑scale backend infrastructure.
  
  

• Strong fundamentals in distributed systems architecture, design patterns, and algorithms.
• Deep programming expertise in Java, including JVM internals, memory models, and garbage collection.
• Proven experience in JVM performance tuning, profiling, and diagnosing performance bottlenecks.
• Strong understanding of concurrency, networking, sockets, OS internals, and performance optimization.
• Hands-on experience building and operating large‑scale distributed systems.
• Experience with relational databases such as Oracle, MySQL, or PostgreSQL.
  
  

• Experience with large‑scale deployments of Kafka, or similar streaming platforms.
• Deep knowledge of stream processing, topic design, partitioning, replication, and HA strategies.
• Experience working within DevOps environments for operationalizing distributed platforms.
• Demonstrated experience architecting and delivering full‑stack Data Lake solutions.
• Strong expertise in designing and operating data ingestion pipelines using:
• Apache Iceberg (tables, catalogs, schema evolution, metadata management)
• Kafka Connect (source/sink connectors, distributed mode)
• Apache Kafka (high‑scale clusters, topic/partition strategies, HA)
• Apache Flink (stateful stream processing, exactly‑once semantics)
• Apache Spark (batch & streaming jobs, optimization, partitioning)
• Expertise in data formats such as Parquet, ORC, and Avro, along with compaction and governance strategies.
• Ability to build scalable, fault‑tolerant ingestion and transformation workflows.
• Experience integrating Data Lakes with analytics engines, query services, or ML platforms.
  
  

Additional Information

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.

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