Data Engineer
San Francisco · San Francisco, California, United States
- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering — team source
Department: Engineering
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require visa sponsorship to work in the United States?
From the employer’s application form
What you’ll work on
Full postingBuild, deploy, and operate production Spark data pipelines on Databricks
Turn analytics-product needs into pipeline requirements with quality and freshness expectations
Set up monitoring and observability so pipeline reliability is measured
Diagnose performance and cost problems and fix their root causes
Recommend pragmatic standards for running pipelines as data and platform scale
From the employer’s posting
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.
Tools in this posting
- Python
- SQL
- AWS
- Databricks
- Spark
- PostgreSQL
Source — Tool mentions in context
- 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.
- 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).
- Experience building RAG pipelines. - AWS infrastructure experience. - Platform administration experience: roles, permissions, access controls, and visibility management.
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
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.
Nice to have - Familiarity with the Databricks ecosystem. - Experience with streaming pipelines and logical replication, such as replicating Postgres into Databricks.
- Familiarity with the Databricks ecosystem. - Experience with streaming pipelines and logical replication, such as replicating Postgres into Databricks. - Experience building RAG pipelines.
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.
Posting record
Report an errorActively hiringFirst seen by us 12 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 18, 2026 · 12 days ago
- Recorded sightings
- 15
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Oct 16, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Monaco is building an AI-native revenue platform that replaces the fragmented GTM stack - CRM, sequencing, call recording, enrichment, pipeline management with one unified system, consolidating 6–10 disconnected tools into a single platform built for the AI era.
We launched publicly in Feb 2026, are already 65 people, and have strong early product-market fit generating millions in ARR within months of launch. You'll have the chance to both scale our core systems and build new features from 0 to 1.
We've raised $85M in our Series B from Founders Fund, Benchmark, and Human Capital, and our founders previously led Brex, Apollo, and Clari.
Come join us if you want to be part of a high autonomy, high pace team reinventing one of the biggest categories in enterprise software.
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.
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
San Francisco, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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