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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 next-generation distributed systems and data lake platforms. This is a hybrid role requiring 2 days per week in a ServiceNow office (San Diego, San Francisco, Pleasanton, or Santa Clara, CA).
You will architect and design high-performance distributed systems and platform components, build scalable data ingestion solutions with emphasis on quality and operational excellence, and deliver clean, modular, reusable code while enforcing engineering best practices. You'll build foundational libraries and frameworks focused on modularity and maintainability, collaborate across engineering teams to refine requirements and deliver end-to-end solutions, provide technical leadership for complex projects, research and evaluate new technologies, and troubleshoot production issues across distributed systems.
The role involves deep expertise in distributed systems architecture, JVM performance tuning, Kubernetes, Apache Iceberg, Kafka, Flink, and Spark. You'll work on large-scale deployments, design fault-tolerant and HA strategies, and integrate data lakes with analytics engines and ML platforms. Experience with relational databases (Oracle, MySQL, PostgreSQL), security systems, and DevOps/GitOps practices is essential.
This position 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.
QUALIFICATIONS:
- 12+ years 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 tools, workflow automation, reasoning about AI's impact on software/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 JVM performance tuning, profiling, and bottleneck diagnosis experience
- Deep hands-on experience with Helm (charts authoring, templating, overlay management)
- 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, PostgreSQL)
- Security systems, methods, and protocols knowledge
- Experience with large-scale distributed systems deployments
- Deep knowledge of replication, fault-tolerance, and HA strategies
- DevOps environment experience to operationalize distributed platforms
- GitOps and release engineering for distributed Kubernetes-native services
- Strong expertise in Kubernetes (workload deployments, upgrades, monitoring, maintenance)
- Strong expertise in Apache Iceberg (tables, catalogs, data encryption, schema evolution, metadata management)
- Strong expertise in Apache Kafka (high-scale clusters, topic/partition strategies, HA)
- Strong expertise in Apache Flink (stateful stream processing, exactly-once semantics)
- Strong expertise in 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
