Staff Data Engineer: Lead AI Telemetry Platform (Remote)

Cribl; Trenton (NJ); Remote; USD 170,000 - 220,000; Full time

Benefits offered by this job

Health insurance

Dental and vision

Short-term disability

Life insurance

Paid holidays & PTO

Fertility treatment benefit

401(k)

Equity

Job summary

Cribl is seeking a Staff Data Engineer to lead data systems and architecture across analytics, data science, and operations, shaping scalable pipelines and governance. The role blends Snowflake, SQL, and dbt with AWS infrastructure and self-hosted orchestration to deliver resilient, cost-aware data platforms.

You will mentor engineers, drive technical direction, partner with stakeholders, and champion AI-driven workflows while ensuring secure, compliant engineering practices across Cribl's data

Qualifications

• Deep expertise in Snowflake data modeling, performance tuning, and cost management.
• Proven technical leadership, setting direction and delivering complex systems.
• Strong Python and SQL fundamentals with ELT and data modeling experience.

Responsibilities

• Lead data engineering initiatives and own architecture for core data systems.
• Collaborate with stakeholders across data, analytics, and security teams.
• Mentor engineers and drive standard practices in testing, logging, and CI/CD.
• Own and operate self-hosted orchestration and cloud infra on AWS.
• Drive dbt practice and warehouse cost/performance at scale.

Skills

Snowflake data modeling

Technical leadership

Python

SQL

ETL/ELT design

AWS

Terraform

CI/CD practices

AI/LLM workflows

Tools

Airflow

Dagster

Prefect

dbt

Terraform

Job description

Cribl is seeking a Staff Data Engineer to lead data systems and architecture across analytics, data science, and operations, shaping scalable pipelines and governance. The role blends Snowflake, SQL, and dbt with AWS infrastructure and self-hosted orchestration to deliver resilient, cost-aware data platforms.

You will mentor engineers, drive technical direction, partner with stakeholders, and champion AI-driven workflows while ensuring secure, compliant engineering practices across Cribl's data