Senior Staff Data Platform Engineer - Apache Iceberg - Apache Spark

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. Role Summary 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. 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. 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. For positions in this location, we offer a base pay of $181,200 - $317,100 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. 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.   Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity,  veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.   Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable