Staff Data Engineer- Cribl
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
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.
Qualifications :
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 AIs 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
Additional Information :
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Accommodations
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Remote Work :
No
Employment Type :
Full-time
Key Skills
- Computer Science
- Docker
- Kubernetes
- Python
- VMware
- C/C++
- Go
- System Architecture
- gRPC
- OS Kernels
- Perl
- Distributed Systems
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