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Salary: USD 181,200 - 317,100 / annual
ServiceNow's Data Platform group is seeking a Senior Staff Engineer (IC5) to architect and deliver large-scale distributed platform components for data-in-motion and backend storage systems. You will lead complex technical initiatives, define engineering best practices, and drive next-generation platform innovation for customers operating at massive scale.
In this role, you will architect and design high-performance distributed systems and platform components; build distributed systems data ingestion solutions with emphasis on scalability, quality, and operational excellence; deliver high-quality, modular, and reusable code while enforcing engineering best practices including code reviews, unit testing, automation, and design reviews; build foundational libraries, frameworks, and tools focused on modularity, extensibility, 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 and evaluate new technologies to enhance platform capabilities; and troubleshoot and diagnose complex production issues across distributed systems.
This is a hybrid position requiring 2 days per week in a ServiceNow office (locations include San Francisco, Pleasanton, Santa Clara, or San Diego, CA). The role supports US Regulated Markets and requires passing USFedPASS (US Federal Personnel Authorization Screening Standards), including background check, credit check, criminal/misdemeanor check, and drug test. Only US citizens, naturalized US citizens, or US Permanent Residents (green card holders) will be considered due to federal requirements.
REQUIREMENTS:
- 12+ years of hands-on engineering experience in distributed systems, data platforms, or large-scale backend infrastructure with a Bachelor's degree; OR 8+ years with a Master's degree; OR 6+ years with a PhD; OR equivalent work experience
- Experience leveraging or critically thinking about how to integrate AI into engineering work (AI-powered coding/operational tooling, workflow automation, or reasoning about how AI changes software and infrastructure development)
- 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
- Deep programming expertise and hands-on experience with Helm (charts authoring, templating, managing overlay layering)
- 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 (Oracle, MySQL, or PostgreSQL)
- Security systems, methods, and protocols knowledge
- Experience with large-scale deployments of distributed systems
- Deep knowledge of replication, fault-tolerant, and HA strategies
- Experience in DevOps environments to operationalize distributed platforms, including GitOps and release engineering for distributed k8s-native services
- Strong expertise designing and architecting platforms using: Kubernetes (workload deployments, upgrades, monitoring, maintenance), Apache Iceberg (tables, catalogs, data encryption, schema evolution, metadata management), Apache Kafka (high-scale clusters, topic/partition strategies, HA), Apache Flink (stateful stream processing, exactly-once semantics), and Apache Spark (batch & streaming jobs, optimization, partitioning)
- Expertise in data formats (Parquet, ORC, Avro) and compaction/governance strategies
- Ability to build scalable, fault-tolerant ingestion and transformation workflows
- Experience integrating Data Lakes with analytics engines, query services, or ML platforms
