Growth Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Growth Engineer San Francisco, California, United States The Role You'll be our first dedicated growth engineer, building the data foundation that every team at Comfy will rely on. We stood up the basics of a data stack recently now we need someone to take ownership of it and turn it into something the whole company trusts. This means designing dimensional models, establishing dbt standards, building pipeline observability, and making data self-serve for product, BizOps, growth, and engineering. You'll work across Comfy Cloud usage, open-source telemetry, Registry activity, GPU scheduling, and billing data. Our stack includes Snowflake and dbt, but we care way more about your ability to learn and ship than whether you've used these exact tools before. You might be a good fit if - You've owned a data warehouse end-to-end and built the modeling standards that kept it trustworthy as things scaled - You care about data quality enough to write the tests before anyone asks you to - You're comfortable working directly with non-technical stakeholders to define metrics, resolve ambiguity, and build models people can actually self-serve against - You instinctively reach for automation to eliminate toil, not because it's trendy, but because life is short - You've shipped dimensional models that survived contact with stakeholders who kept changing their minds What you'll do - Own the warehouse end-to-end. Design dimensional models, establish dbt conventions, and build datasets that serve analytics, product, and finance - starting with unifying Comfy Cloud events, open-source install metrics, and Registry activity

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