Staff Data Engineer - Cribl

Staff Data Engineer

We are seeking a highly skilled Staff Engineer with strong expertise in Cribl Pipelines and data streaming to lead the design, development, and optimization of our observability and data engineering workflows. The ideal candidate will bring hands-on experience with Cribl Stream/Edge, advanced ETL practices, real-time streaming frameworks (Spark, Flink, Kafka), and deep knowledge of observability platforms (Splunk, Prometheus, Grafana, TSDBs). This role is both technical and strategic, requiring deep problem-solving skills, architectural vision, and the ability to mentor and guide engineering teams.

What you get to do in this role:

• Cribl Pipelines: Architect and optimize large-scale data pipelines using Cribl Stream and Cribl Edge for ingestion, transformation, and routing.
• Streaming & Real-Time Processing: Design and implement real-time data pipelines using Apache Spark, Apache Flink, and Kafka Streaming to handle high-throughput, low-latency observability data.
• ETL/Data Engineering: Apply advanced ETL practices to cleanse, enrich, filter, and normalize diverse data sources before downstream ingestion.
• Observability Data Management: Manage high-volume telemetry data (logs, metrics, traces, events) and design strategies for noise reduction, performance optimization, and cost control.
• Integration: Build robust integrations with Splunk, Elasticsearch, Kafka, S3, Prometheus, VictoriaMetrics, InfluxDB, and other TSDBs.
• Scalability & Performance Tuning: Ensure Cribl and streaming pipelines perform reliably at scale, handling high-cardinality and high-throughput datasets.
• Best Practices & Governance: Define and enforce observability ingestion best practices, schema governance, and data quality standards.
• Leadership & Mentorship: Guide engineers in pipeline design, streaming technologies, and observability best practices.
• Innovation: Explore emerging technologies in observability, streaming, and AI-driven analytics to continuously improve architecture.

To be successful in this role you have:

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
• 10+ years of software/data engineering experience, with at least 5+ years hands-on in Cribl (Stream/Edge).
• Strong background in ETL pipelines, real-time streaming, and distributed data processing.
• Hands-on expertise with Apache Spark (Structured Streaming), Apache Flink, and Kafka Streaming.
• Deep understanding of observability data (logs, metrics, traces) and platforms such as Splunk, Elastic, Prometheus, Grafana, OpenTelemetry.
• Experience with Time Series Databases (TSDBs) such as VictoriaMetrics, InfluxDB, TimescaleDB, or ClickHouse.
• Proficiency in scripting/programming (Python, Go, or Java) for pipeline extensions and automation.
• Strong knowledge of Kafka, S3, cloud-native services (AWS/GCP/Azure) for data transport and storage.
• Experience with scalability, performance tuning, and cost optimization in observability pipelines.
• Strong collaboration and leadership skills to influence cross-functional teams.
• Exposure to AI/ML-based anomaly detection or predictive observability use cases.

• Previous Staff/Principal Engineer experience in large-scale data systems.

FD21

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, 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.

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.