Senior Staff Data Platform Engineer - Kafka - Apache Iceberg - Apache Spark

ServiceNow•San Diego, CA

3d•$181,200 - $317,100•Hybrid

About The Position

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. 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.

Requirements

Experience leveraging or critically thinking about how to integrate AI into engineering work — whether using AI-powered coding and operational tooling, automating workflows, or reasoning about how AI changes the way software and infrastructure are built.
10+ years of software development experience with a Bachelor's degree; OR 8+ years with a Master's degree; OR 6+ years with a PhD OR equivalent work experience.
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.

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.