Data Engineer

Zafran is building the next generation of vulnerability and risk management. We’re moving the analytical heart of our investigation product from various of DBs into ClickHouse - and we need a Senior Data Engineer to be the owner, builder, and guardian of that warehouse.This is the team’s first dedicated data engineering hire. You’ll set standards, build new pipelines, and partner closely with the engineers who power our customer-facing dashboards and investigation data layer.

About Zafran:

Our Mission: To stop the exploitation of vulnerabilities, everywhere.

What makes us different: Zafran de-risks 90% of critical vulnerabilities overnight across your hybrid environment and utilizes Agentic Capabilities and your existing security tools to rapidly mitigate and remediate the 10% most likely to be exploited.

​​Who’s behind us: Zafran is backed by Menlo Ventures, Sequoia Capital, Cyberstarts, and a deep belief that cybersecurity should move as fast as attackers do. We’re one of the fastest-growing companies in the industry, scaling to meet demand from the world’s most advanced, security-obsessed organizations.

We’re serious about our mission- so expect work that matters, teammates who challenge and inspire you, and plenty of fun along the way!

What you will do:

• Build and own Zafran’s ClickHouse analytics platform - schemas, ingest, pipelines, and the services that drive them.

• Lead migrations moving all data types onto ClickHouse, end-to-end.

• Set the standard for schema design, migration safety, and query patterns. Review designs before they land.

• Profile and optimize queries powering data investigation all over the platform - design materialized views, projections, and rewrites where they help.

• Own ingest reliability - Kafka-to-ClickHouse ingestion, backfill tooling, and tenant-aware data quality monitoring.

• Manage cost and capacity as data volume grows - storage tuning, query-cost monitoring, capacity planning across many tenants.

• Educate the team - write playbooks, run design reviews, raise the bar on how the engineering org thinks about analytical data.