Staff Data Engineer

Responsibilities

• 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.
• 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.
• Partner with the Data Engineering manager to set technical direction. Shape the platform roadmap, engineering standards, and build-vs-buy/architectural tradeoffs.
• 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.

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