Senior Staff Data Platform Engineer - Apache Iceberg - Apache Spark

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.
Join us to put AI to work for people.

Responsibilities

Position Location:; This is a Flexible (Hybrid) position. Flexible positions require 2 days per week in a ServiceNow office location. We have offices in several locations, including San Francisco, CA; Pleasanton, CA; Santa Clara, CA; San Diego, CA; Please Note: This position will include supporting our US Regulated Markets.; Team Overview; Role Summary; What you get to do in this role:; 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.

Requirements

To be successful in this role you have:; 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. Core Distributed Systems 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. Specific Distributed Systems Expertise; 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); 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.