Senior Cribl Engineer / Security Data Engineer
At a glance
Senior Data Engineering role at TSG Risk Management. Remote, United States · full-time · no salary stated · we estimate $128,000–$165,575.
TSG Risk Management has not published a salary for this role. The figure below is our estimate, not theirs.
remoteroles summary, based on the employer's posting.
What you'll do
- Build and maintain Cribl LogStream pipelines, adjusting how data moves, changes, gains context and meets quality needs
- Link Cribl with AWS, SIEM and security analytics systems, and streamline automated data intake and onboarding
- Check security telemetry before it supports SIEM, detection engineering, threat hunting, incident response and analytics
- Create Snowflake objects, from databases and tables to tasks, procedures and protected data-sharing arrangements
- Watch pipeline performance, fix faults, document configurations and data flows, and make ongoing refinements
What you bring
- At least three years configuring and administering Cribl LogStream and developing its pipelines
- At least two years handling Snowflake administration, architecture and data engineering in large enterprise settings
- You have built or supported high-volume security data pipelines using Snowflake, Databricks or similar platforms
- You have automated pipeline tasks with a scripting language such as Python or JavaScript
Who this fits
This senior engineering role suits someone with deep Cribl and Snowflake experience who can diagnose difficult pipeline issues and work across security and data teams. Charlotte is the preferred location; applicants from New York City, Los Angeles, Southern California or elsewhere may also be considered. The work arrangement can be hybrid or remote.
From the employer
Senior Cribl Engineer / Security Data Engineer
Location: Charlotte, NC preferred. Candidates in New York City, Los Angeles, Southern California, or other locations may also be considered.
Work Model: Flexible hybrid or remote
Position Overview
Seeking an experienced Senior Cribl Engineer / Security Data Engineer to develop, maintain, and optimize scalable data pipelines utilizing Cribl LogStream. The ideal candidate should have deep knowledge of Cribl architecture, extensive hands-on experience in data engineering, and the ability to improve data ingestion and processing workflows. Familiarity with security operations, SIEM platforms, the Open Cybersecurity Schema Framework (OCSF), security log data, AWS cloud services, and modern data platforms such as Snowflake and Databricks is highly desirable.
Responsibilities
- Develop, implement, and maintain data processing pipelines within Cribl LogStream.
- Configure and optimize data routing, transformation, enrichment, filtering, normalization, and data quality processes.
- Develop and support integrations between Cribl, AWS, SIEM platforms, security analytics tools, and enterprise security lake data platforms.
- Build, troubleshoot, and optimize automated data ingestion and onboarding workflows.
- Onboard and validate security telemetry for SIEM, detection engineering, threat hunting, incident response, and security analytics use cases.
- Collaborate with Security Operations, Detection Engineering, Data Engineering, Infrastructure, and Analytics teams to deliver reliable, scalable, and high-quality data solutions.
- Monitor pipeline performance, resolve issues, and implement continuous improvements.
- Document pipeline configurations, operational procedures, and data flows.
- Develop, create, and maintain Snowflake database objects including databases, schemas, tables, views, streams, tasks, stored procedures, and secure data-sharing configurations.
Qualifications
- 3+ years of experience with Cribl LogStream administration, configuration, and pipeline development.
- 2+ years of hands-on experience with Snowflake administration, architecture, and data engineering in large-scale enterprise environments.
- Experience designing and supporting large-scale security data ingestion, transformation, and processing pipelines utilizing platforms such as Snowflake and Databricks.
- Experience with scripting languages (e.g., Python, JavaScript) for pipeline automation.
- Experience onboarding and managing enterprise security data within SIEM, security data lake, or security analytics environments.
- Familiarity with OCSF, security data normalization, governance, compliance, and other security telemetry best practices.
- Excellent problem-solving skills, ability to debug complex pipeline issues, and strong analytical thinking
- Experience designing, creating, and managing Snowflake databases, schemas, tables, views, streams, tasks, stored procedures, and data pipelines
- Experience with Snowflake Cortex, Snowpark, Python UDFs, stored procedures, and advanced automation frameworks.
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