C

Cribl

Data observability platform for logs

Staff Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • Deep expertise in Snowflake, including advanced data modeling, query and warehouse performance tuning, cost management, and security/RBAC design.
  • Experience as a tech lead or staff-level engineer setting direction, driving architecture, and delivering complex systems across a team.
  • Ability to work across data, engineering, and business teams and lead through influence.
  • A track record of growing junior and mid-level engineers through coaching, review, and pairing.
  • Strong Python and SQL fundamentals, with solid ELT patterns and data modeling experience.
  • Hands-on experience operating self-hosted or self-managed orchestration, including owning upgrades, workers, and the operational footprint; Prefect is preferred, and equivalent experience running Airflow or Dagster on one's own infrastructure is acceptable.
  • Hands-on AWS and infrastructure-as-code experience building cloud infrastructure with Terraform or equivalent using predictable, maintainable patterns.
  • Experience building cloud applications or backend services, including APIs, ingestion services, and event-driven workflows.
  • Experience with production-grade engineering practices, including logging, alerting, versioning, and CI/CD.
  • Fluency building with AI-assisted development platforms such as Claude Code, with demonstrated ability to use them to accelerate delivery.

Responsibilities

  • Serve as 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, including Data Analysts, SREs, IT Engineers, and business teams, to clarify requirements, validate outputs, and communicate risks, tradeoffs, and timelines proactively.
  • Own and operate the self-hosted orchestration platform, including evolving the self-managed Prefect deployment and its build/worker system, operational hygiene, upgrade path, and cost/footprint tradeoffs of a hybrid, self-hosted model.
  • Own the Snowflake environment as subject-matter expert on data modeling, performance, and cost optimization, including RBAC/permissions design, permissions tooling, and governance.
  • Build, operate, and monitor 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 dbt practice, including the in-flight dbt Fusion migration, and own warehouse cost/performance at scale.
  • Develop cloud-native services and infrastructure on AWS, including ingest/API services, event-driven ingestion, upsert patterns, package reuse, and supporting infrastructure-as-code.
  • Advance the infrastructure-as-code practice using Terraform or similar by building 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 and engineering standards, and make build-vs-buy and architectural tradeoffs.
  • Mentor and grow data engineers through code review, pairing, design feedback, and coaching to develop junior and mid-level engineers.
  • Support data science and agentic initiatives by preparing model-ready datasets, exposing features, and integrating AI/LLM workflows into production.
  • Contribute to secure, compliance-minded engineering practices in collaboration with IT and Security.

Desired Qualifications

  • Prefect experience is strongly preferred; equivalent experience running Airflow or Dagster on one's own infrastructure is acceptable.

About the Company

Cribl

Data observability platform for logs

Cribl helps tech teams manage and understand their data through data observability. Its two main products, Cribl Stream and Cribl Edge, collect, route, transform, and analyze logs, metrics, and other observability data. Edge gathers real-time data from network edge devices, sending it to Stream or other destinations for processing. Stream routes and transforms data on-premises or in the cloud and forwards it to destinations, with integrations like Office 365 and Microsoft Azure to monitor activity and security. The goal is to give teams real-time visibility into data, improve operational efficiency, and strengthen security by managing data flows and observability insights.

Company size
1,001-5,000
Company stage
Series E
Total funding
$596.4M
Headquarters
San Francisco, CA
Founded
2018

Recently Posted Jobs

Explore more opportunities at Cribl

See more jobs