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ServiceNow's Data Platform group is seeking a Senior Staff Engineer (IC5) to architect and deliver next-generation distributed systems and data platform capabilities. The team builds highly scalable, high-performance platform solutions for data-in-motion and backend storage systems, serving customers operating at massive scale with extreme demands on data volume, throughput, and concurrency.
In this role, you will architect and design large-scale distributed platform components, lead complex technical initiatives across the organization, and define engineering best practices. You will be responsible for building distributed systems data ingestion solutions with emphasis on scalability, quality, and operational excellence. Key responsibilities include delivering high-quality, modular, and reusable code while enforcing engineering best practices such as code reviews, unit testing, automation, and design reviews. You will build foundational libraries, frameworks, and tools focused on modularity, extensibility, configurability, and maintainability.
You will 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 complex production issues across distributed systems.
This is a hands-on technical leadership role where you will combine deep engineering expertise with the ability to guide and influence large-scale platform initiatives. You will work in a DevOps environment to operationalize distributed platforms and integrate data lakes with analytics engines, query services, and ML platforms.
**Requirements:**
**Experience Level:**
- 15–20 years of hands-on engineering experience in distributed systems, data platforms, or large-scale backend infrastructure
**Core Engineering Expertise:**
- 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
**Distributed Systems Expertise:**
- Experience with large-scale deployments of distributed systems
- Deep knowledge of replication, fault-tolerant, and HA strategies
- Experience working in DevOps environments to operationalize distributed platforms
- Strong expertise in designing and architecting platforms using Kubernetes (workload deployments, upgrades, monitoring and maintenance)
- Apache Iceberg (tables, catalogs, schema evolution, metadata management) is a plus
- Apache Kafka (high-scale clusters, topic/partition strategies, HA) is a plus
- Apache Flink (stateful stream processing, exactly-once semantics) is a plus
- Apache Spark (batch & streaming jobs, optimization, partitioning) is a plus
- 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
