Staff Data Engineer - Data Platform Lead (Remote, Equity)

Cribl; Springfield (IL); Remote; USD 170,000 - 220,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Short-term disability

Life insurance

Paid holidays

Paid time off

Fertility treatment benefit

401(k)

Equity

Job summary

Cribl is seeking a Staff Data Engineer to lead data engineering efforts across analytics, data science, and operational decision-making. You will influence architecture, model-ready data, and AI/LLM workflows while partnering with analytics, SRE, and IT teams in a remote-first environment.

The role emphasizes ownership of Snowflake, dbt, Prefect, and Terraform-based infrastructure, with a focus on cost, performance, and governance. Strong leadership and mentoring are essential.

Qualifications

• Strong Python and SQL fundamentals with data modeling experience.
• Experience with ELT patterns and warehouse cost optimization.
• Proven ability to mentor engineers and lead cross-functional teams.
• Hands-on experience with self-hosted/orchestrated data pipelines and cloud infra.

Responsibilities

• Serve as a technical lead for the Data Engineering team.
• Own architecture and design decisions for core data systems and drive reliable, production-grade outcomes.
• Partner with stakeholders across functions (Data Analysts, SREs, IT Engineers, and business teams).
• Clarify requirements, validate outputs, and communicate risks, tradeoffs, and timelines proactively.
• Own and operate our self-hosted orchestration platform.
• Run and evolve our self-managed Prefect deployment and its build/worker system.
• Own the operational hygiene, upgrade path, and cost/footprint tradeoffs of running orchestration on a hybrid, self-hosted model.
• Own Cribl's Snowflake environment.
• Serve as the subject-matter expert on data modeling, performance, and cost optimization, and own RBAC/permissions design, permissions tooling, and governance.
• Build, operate, and monitor the core data tech stack. This covers data pipelines, ingestion services, integrations, and the warehouse, ensuring data is accurate, timely, and trusted, with logging, alerting, and observability as first-class concerns.
• Advance the modern data stack.
• Drive our dbt practice forward, including the in-flight dbt Fusion migration, and own warehouse cost/performance at scale.
• Develop cloud-native services and infrastructure on AWS. This includes our ingest/API services (event-driven ingestion, upsert patterns, package reuse) and the IaC that supports them.
• Advance our infrastructure-as-code practice (Terraform or similar).
• Build reusable modules, clean deployment patterns, CI integration, and strong operational hygiene, including self-hosted/hybrid deployment patterns.
• Partner with the Data Engineering manager to set technical direction.
• Shape the platform roadmap, engineering standards, and build-vs-buy/architectural tradeoffs.
• Mentor and grow data engineers through code review, pairing, design feedback, and coaching that levels up junior and mid-level engineers.
• Support Cribl's growing data science and agentic initiatives.
• Prepare model-ready datasets, expose features, and integrate AI/LLM workflows into production.
• Contribute to secure, compliance-minded engineering practices in collaboration with IT/Security.

Skills

Python

SQL

Data modeling

ELT patterns

Cross-functional collaboration

Mentoring engineers

Production-grade engineering

Snowflake

dbt

Airflow

Dagster

Prefect

Terraform

AWS

Education

Bachelor's degree or equivalent

Tools

Snowflake

dbt

Prefect

Airflow

Dagster

Terraform

Job description

Cribl is seeking a Staff Data Engineer to lead data engineering efforts across analytics, data science, and operational decision-making. You will influence architecture, model-ready data, and AI/LLM workflows while partnering with analytics, SRE, and IT teams in a remote-first environment.

The role emphasizes ownership of Snowflake, dbt, Prefect, and Terraform-based infrastructure, with a focus on cost, performance, and governance. Strong leadership and mentoring are essential.