Senior Staff Data Engineer - Cloud Analytics & FinOps Engineering Platform

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

Team:

Join the Global Cloud Services organization as a founding member of our Cloud Analytics & FinOps Engineering Platform team. You will work closely with our Principal Software Developer and Principal DevOps Engineer to establish the data engineering foundation for ServiceNow's next-generation FinOps governance platform.

Role:

We are building a modern, secure, and highly scalable multi-cloud data platform infrastructure powering next-generation analytics to support ServiceNow's Cloud and AI growth. As our Principal Data Engineer for Cloud Analytics & FinOps Engineering Platform, you will architect, implement, and optimize the core data warehousing, transformation, and ETL infrastructure that powers our FinOps governance capabilities. You will serve as the primary FinOps engineering point of contact across ServiceNow engineering teams, translating functional requirements into scalable technical solutions while establishing data engineering best practices for enterprise-scale cost analytics.

This is a unique opportunity to build enterprise-grade data infrastructure from the ground up, drive technical leadership across teams, and establish ServiceNow as a thought leader in the FinOps space.

What you get to do in this role: 

Data Architecture & Engineering Leadership

• Design and implement scalable data warehousing solutions supporting petabyte-scale cost and usage analytics across AWS, GCP, Azure, and private data centers.
• Architect robust ETL/ELT pipelines using Apache Airflow, dbt, and modern orchestration frameworks for complex multi-cloud data ingestion and transformation.
• Establish data modeling best practices for cost allocation, showback/chargeback, and unit economics analysis while ensuring data quality, lineage, and governance across the platform.

Technical Translation & Cross-Team Collaboration

• Serve as the primary FinOps engineering point of contact across ServiceNow engineering teams, translating functional requirements from finance, product, and business stakeholders into comprehensive technical specifications.
• Collaborate with Software Developers and DevOps Engineers to coordinate implementation and delegate technical work across development and infrastructure teams.
• Drive technical decision-making on data architecture, tool selection, and implementation approaches while ensuring alignment with enterprise standards.

Hands-On Implementation & Optimization

• Build and optimize distributed query engines using Trino/Presto for complex analytics workloads across multi-cloud environments.
• Implement advanced data transformation logic using dbt for cost attribution, resource optimization, and financial analytics.
• Develop high-performance data ingestion connectors for hyperscaler billing APIs, ServiceNow internal systems, and enterprise financial systems.
• Optimize query performance and resource utilization for large-scale analytics workloads while maintaining strict SLAs.

FinOps Engineering Excellence

• Design and implement enterprise-grade showback/chargeback systems enabling detailed cost attribution across departments, projects, and services.
• Build automated cost optimization workflows and anomaly detection systems for proactive resource management.
• Establish data-driven insights for cloud cost forecasting, budget management, and resource rightsizing recommendations.
• Create self-service analytics capabilities enabling engineering teams to understand and optimize their cloud spend.

Platform Integration & Data Governance

• Implement comprehensive metadata management using Hive Metastore and Iceberg-compatible catalogs for data discovery and lineage tracking.
• Establish data quality frameworks with automated validation, monitoring, and alerting for critical financial metrics.
• Design secure data access patterns and implement role-based access controls for sensitive cost and usage data.
• Build integration layers connecting cost data with ServiceNow's broader analytics and bu