Principal Data Platform Software Engineer (RaptorDB)

ServiceNow•Santa Clara, CA

2d•$240,100 - $420,200•Flexible

About The Position

About RaptorDB Operations RaptorDB Operations owns the tooling, and operational excellence that safely deploys, manages, and operates RaptorDB databases across ServiceNow's global data centers and public cloud providers. Our team delivers mission-critical solutions that enable reliable service for millions of ServiceNow customers at massive scale. We partner closely with RaptorDB development team, infrastructure automation, systems engineering, security, and customer support teams to architect and implement database operations that meet rigorous standards for uptime, performance, and resilience. Role Overview As a Principal Data Platform Software Engineer, you take part in architecting solutions for operating RaptorDB at scale. You will take part in setting technical directions for database deployment strategies, lead cross functional design sessions and establish best practices across teams. This role combines hands-on engineering excellence with technical leadership, bridging on-premise technologies, cloud-native architecture, infrastructure automation, and operational resilience.

Requirements

Skilled in applying AI-assisted tools to enhance productivity across design, analytics, and software development while adhering to governance and best practices.
Experience in working across organizations co-architecting and co-designing holistic solutions.
Track record of helping with setting technical direction, making architectural decisions under uncertainty in a highly collaborative environment.
Deep expertise with databases, including operations, operational management and backup/restore strategies.
Experience designing and building distributed systems, with strong understanding of high-availability, failover, and disaster recovery architectures.
Exceptional communication skills; ability to articulate complex technical concepts to both engineering and non-technical audiences.
Experience in leveraging or critical thinking about how to integrate AI into work processes, decision making, or problem solving. This includes using AI powered tools, automated workflows, analyzing AI-driven insights, or reasoning about AI’s impact on how infrastructure is built and run.
12+ years of software engineering experience, with 8+ years focused on database systems, infrastructure, or cloud platforms.
Hands-on proficiency with multiple programming languages (Go, Python, or equivalent) and demonstrated mastery of software engineering best practices.
Experience with Kubernetes and database operators.
Experience operating databases in cloud environments
In-depth Linux knowledge
Excellent technical problem-solving skills

Nice To Haves

Background in open-source database is a plus

Responsibilities

Participate in architecting and designing solutions for RaptorDB deployment, operations, and resilience across ServiceNow's hybrid infrastructure (datacenters and public cloud providers).
Collaborate across organizational boundaries to evolve backup, restore, replication, and failover systems that integrate with broader database reliability and scalability efforts across the platform.
Drive adoption of cloud-native technologies (e.g., Kubernetes, Cloud-Native PostgreSQL) and establish reference architectures that balance operational simplicity with business requirements.
Develop high-quality, clean, and maintainable code that enforces best practices in software architecture, automated testing, code reviews, and deployment pipelines.
Collaborate with Architects across teams, RaptorDB development, infrastructure automation, systems engineering, and security teams to ensure database operations are secure, performant, and resilient across all environments.
Lead performance analysis and optimization initiatives, including backup and restore times, recovery time objectives (RTO), and resource utilization across the fleet.
Respond to urgent production incidents and provide expert guidance on database operations challenges to customer-facing and internal teams.
Build and maintain institutional knowledge through documentation, runbooks, and architectural decision records that enable the team to scale.