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Salary: USD 171,900 - 300,800 / annual
ServiceNow is seeking a Senior Staff Software Engineer to lead the Workflow Data Fabric (WDF) platform organization. WDF connects the ServiceNow AI Platform to enterprise data wherever it lives—querying it in place, streaming it in real time, and ingesting it at scale so workflows and AI agents act on trusted, current data.
You will serve as a senior technical leader across multiple scrum teams, setting architecture direction while remaining hands-on in the code. You will own the hardest performance, scalability, and reliability problems across data-access and data-movement products. Zero Copy Connectors and Remote Process Sync are the anchor areas for this role, with cross-team technical leadership spanning Data Fabric, Trino-based connectors, Stream Connect, ETL/Import Sets, Analytics Ingestion, and data quality.
Key responsibilities include:
- Own end-to-end architecture for Zero Copy Connectors: the federated query path from the ServiceNow platform through a Trino-based query engine to external warehouses and lakehouses (Snowflake, Databricks, BigQuery, Redshift, Oracle, Iceberg), including pushdown, connection pooling, caching, authentication, and connector-framework extensibility.
- Own the technical direction of Remote Process Sync, driving throughput, parallel processing, ordering guarantees, resiliency, and supportability for high-volume customer and product integrations.
- Drive the architecture of Private Connectivity (Reverse Tunnel), which gives the platform secure, outbound-initiated access to customer data sources behind firewalls, covering mTLS tunneling, SNI-based routing, stream multiplexing, and enterprise-scale resiliency.
- Provide cross-team technical leadership across the WDF portfolio, ensuring coherent designs, shared frameworks, and consistent security and governance patterns.
- Lead architecture and design reviews; write and approve technical specifications; make and document build-vs-buy, protocol, and platform trade-offs.
- Write production code in critical paths, prototype new approaches, and review code across teams.
- Define and drive performance and scalability strategy: benchmarks, capacity models, and end-to-end performance validation.
- Serve as the senior technical escalation point for complex production and customer issues; drive root-cause analysis and turn recurring issues into durable platform fixes.
- Partner with Product Management, Engineering Managers, Quality Engineering, Support, and adjacent platform teams to shape roadmaps and sequence technical investments.
- Mentor and grow senior and staff engineers; build technical depth and knowledge continuity.
REQUIREMENTS:
Required:
- 12+ years of professional software engineering experience, including significant time building and operating large-scale distributed systems or data platforms.
- Deep expertise in distributed systems and data platform fundamentals: query processing, data integration/replication, change data capture, streaming or batch pipelines, concurrency, consistency, and fault tolerance.
- Experience with Kubernetes-based services, multi-tenant SaaS architecture, and data security/governance (ACLs, encryption, data residency).
- Demonstrated track record of leading architecture across multiple teams and delivering complex, cross-functional platform initiatives end to end.
- Strong hands-on coding ability in at least one systems language (Java, C++, Go, Scala, or similar), with continued practice of writing and reviewing production code.
- Proven experience diagnosing and solving performance and scalability problems in production systems, using profiling, benchmarking, and observability data.
- Ability to influence without authority—aligning engineers, managers, product, and partner teams around technical direction through clear written and verbal communication.
- Bachelor's degree in Computer Science or related field, or equivalent practical experience.
Preferred:
- Experience with Trino internals, connector SPI, or other federated/distributed SQL query engines.
- Experience with lakehouse and big-data technologies: Apache Iceberg, Apache Polaris or other Iceberg REST catalogs, Spark, or Delta Lake.
- Experience with Kafka or other event-streaming platforms, CDC, or message-driven integration frameworks.
- Hands-on experience with cloud data warehouses and lakehouses (Snowflake, Databricks, BigQuery, Redshift) and their JDBC/REST access patterns and authentication models (OAuth).
- Experience with the ServiceNow platform (Glide), IntegrationHub, or Flow Designer.
- Hands-on experience owning customer escalations or high-severity production incidents for enterprise software.
- Familiarity with data quality, data observability, or AI-assisted data transformation.
- Open-source contributions, patents, publications.
