Remote Staff Data Engineer: Lead Data Platform & AI

Cribl; Boston (MA); Remote; USD 170,000 - 220,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Equity

Paid holidays

Paid time off

Fertility treatment benefit

Job summary

Cribl is seeking a Staff Data Engineer to lead and shape Cribl's data platform. You will own architecture for core data systems, drive reliability, and partner with analysts, SREs, IT, and business teams to deliver scalable data solutions.

This role combines hands-on engineering with strategic leadership to advance the modern data stack. You will mentor engineers, optimize Snowflake environments, and contribute to cost-aware data modeling while improving observability, logging, and CI/CD

Qualifications

• Deep expertise in Snowflake data modeling, performance tuning, and cost management.
• Strong Python and SQL fundamentals with ELT and data modeling experience.
• Proven track record leading data engineering efforts and mentoring engineers.

Responsibilities

• Lead data engineering initiatives and set technical direction for the team.
• Own architecture and design decisions for core data systems and ensure reliability.
• Collaborate with Data Analysts, SREs, IT engineers, and business teams to align deliverables.
• Mentor junior and mid-level engineers through code reviews and coaching.
• Develop and operate self-hosted orchestration platforms and data pipelines.

Skills

Snowflake data modeling

Python

SQL

Data engineering leadership

Communication

ELT patterns

Tools

Prefect

Airflow

Terraform

Job description

Cribl is seeking a Staff Data Engineer to lead and shape Cribl's data platform. You will own architecture for core data systems, drive reliability, and partner with analysts, SREs, IT, and business teams to deliver scalable data solutions.

This role combines hands-on engineering with strategic leadership to advance the modern data stack. You will mentor engineers, optimize Snowflake environments, and contribute to cost-aware data modeling while improving observability, logging, and CI/CD