Data Engineer

We've raised $85M in our Series B from Founders Fund, Benchmark, and Human Capital, and our founders previously led Brex, Apollo, and Clari.

The role

You'll own the Spark pipelines on Databricks that power Monaco's analytics products, working directly with product teams to turn what they need into reliable, cost-conscious data. This is a hands-on individual contributor role for a mid-level to senior engineer (roughly 2–6 years of experience).

What you'll do

• Build, deploy, and operate production Spark data pipelines on Databricks.
• Partner with product teams to turn analytics-product needs into pipeline requirements, including data quality and freshness expectations.
• Set up monitoring and observability so pipeline reliability is measured, not assumed.
• Diagnose performance and cost problems and fix their root causes.
• Recommend pragmatic standards for running pipelines as our data and platform scale.

What you'll bring

• Hands-on experience building, deploying, and maintaining production Spark pipelines.
• Deep understanding of how concepts like clustering, shuffles, different join strategies, and batch versus stream processing create tradeoffs in performance, freshness, and cost.
• Experience with reliability, monitoring, and observability, and the ability to explain how you diagnosed a real pipeline failure or bottleneck.
• Strong SQL.
• Basic programming skills in any language (Python is a plus).
• Comfort working as an individual contributor, directly with product teams, and through ambiguity.

Nice to have

• Familiarity with the Databricks ecosystem.
• Experience with streaming pipelines and logical replication, such as replicating Postgres into Databricks.
• Experience building RAG pipelines.
• AWS infrastructure experience.
• Platform administration experience: roles, permissions, access controls, and visibility management.

Location

• San Francisco. We're an in-person team - 5 days in the office. At this stage, proximity genuinely accelerates product quality and team cohesion.