Job description

PREFECT prefect.io BUILDS AND OPERATES RESILIENT, PYTHONIC ORCHESTRATION AND MCP PLATFORMS -- PREFECT OSS github.com, PREFECT CLOUD prefect.io, FASTMCP OSS, gofastmcp.com AND HORIZON prefect.io USED FOR MISSION-CRITICAL WORKLOADS. Our Vision: Prefect will define automation for the context era. Our Mission: Curate an intelligent context layer that delivers the right information at the right time. About Prefect Prefect builds automation for an unpredictable world. The last decade of automation was about protecting workflows from unpredictability; in the agentic era, unpredictability is the point. Our mission is to give people confidence in automated work, whether that work is a mission-critical data pipeline or a fleet of AI agents. In August 2026, Prefect and Dagster, competitors for eight years, joined forces to build the next generation of automation infrastructure. Today, our ecosystem includes Dagster, the data platform; Prefect, the agent platform; and FastMCP, the leading open-source developer framework for the MCP ecosystem. Together, our open-source and commercial products are trusted by Fortune 500 companies, data innovators, and high-growth technology companies around the world. We think of our culture as the operating system of the company. We’ve carefully created a supportive, high-performance environment that empowers our team to do the best work of their careers, have meaningful impact, and continue growing personally and professionally. We’re a remote-first team that values high standards, ownership, and thoughtful collaboration. ROLE SUMMARY: We sell two products with two funnels that behave nothing alike. Prefect Cloud and Dagster+ both start with someone running an open source tool on their laptop, and both end either in a self-serve credit card or in a sales conversation with a Fortune 500 data platform team. Between those two points sits our go-to-market data: product telemetry in Amplitude, the warehouse, Salesforce, campaign and channel spend, community signals, and an uncomfortable number of different systems and touch points. You will own the analytics and data modeling for GTM that describe how someone gets from first touch to activated user to paying customer, across both self-serve and sales. You will report to Gabriel Madureira, our Chief Growth Officer, and work day to day with marketing, sales, RevOps, and product. WHAT YOU'LL DO: - Own the go-to-market data model. One definition of an account. One definition of an activated workspace. One definition of pipeline. Version controlled, tested, documented, and deployed by you. - Model the self-serve funnel end to end, from first visit through signup, activation, paid conversion, and expansion, for both Prefect Cloud and Dagster+. Make the drop-off points visible and the cohorts comparable. - Model the sales funnel end to end, from source through MQL, SQL, pipeline, and closed won, including stage conversion and velocity, using Salesforce data as it actually is rather than as the schema claims. - Build attribution that marketing and sales both accept. First touch, last touch, and a multi-touch model, with the assumptions written down so the arguments are about strategy instead of arithmetic. - Build the unit economics. CAC and payback by channel and segment, LTV/CAC, ROI on campaigns and events, self-serve versus sales-assisted. That includes going and getting the spend data nobody has loaded yet. - Ship the reporting layer so go-to-market teammates answer their own questions instead of queuing behind you. We run two Omni instances, one per product. Looker experience transfers directly. - Help us set the go-to-market rhythm. Pipeline reviews, the weekly funnel meeting, board reporting. You'll hear a question before it becomes a ticket, and often you'll be the one who reframes it. YOUR QUALIFICATIONS: Must have - Four or more years building analytics models in dbt on a cloud warehouse, owned in production with tests, CI, and version control. - Strong SQL, plus enough Python for the parts SQL is bad at: API pulls, spend data, one-off enrichment. - Experience building and maintaining a semantic layer in Omni, Looker, or something comparable. We care that you have modeled metrics for other people to use, not that you have built dashboards. - Direct work with go-to-market teams on funnel conversion, attribution, and unit economics like CAC, payback, and ROI, using real CRM data from Salesforce or HubSpot. - Prior knowledge of GTM systems like Salesforce, Amplitude, Segment, Hubspot. - A product-led or self-serve business: activation, trial conversion, PQLs, usage-based revenue. - A background in engineering or data, meaning you write code, read other people's code, and deploy your own work. - Comfort with AI-native development. Nice to have - Product analytics tools, especially Amplitude. - Developer tools or open source, where the funnel starts with a pip install and the top of it is a community rather than a lead list. WHO THIS ROLE IS NOT FOR: - You want to do machine learning or data science. There is plenty of interesting analysis here, but the core of the job is modeling and measurement for go-to-market decisions. - You expect clean data. Amplitude records page context in four different properties depending on where the event came from, and Salesforce carries campaign fields no process writes to anymore. Sorting that out is the work, not an obstacle to it. If finding out that a field has been silently empty for eight months ruins your week, this will be a long year. - You want to take tickets. People will bring you questions like "why did self-serve conversion drop in August," not specifications. You decide what to measure. - You want to manage a team soon. This is an individual contributor role and will be for a while. You get a lot of influence over how go-to-market data works and no direct reports. WHAT YOU'LL GET IN RETURN: Base Salary Ranges: - San Francisco Bay Area & NYC Metro: $173,000–$222,000 - Washington D.C., Boston, LA Metro, Seattle: $162,000–$201,000 - Denver, Chicago, Atlanta, & all other U.S. metros: $154,000–$200,000 Actual base salary within each range depends on the candidate's location, experience, and qualifications. Equity and benefits are not included in the range above. Your recruiter can share more about the salary range for your preferred location during the hiring process. Perks and Benefits: - Remote-first team with flexible-first culture - Equity Stock Options - 401(k) with 5% company match (vests immediately!) - Unlimited PTO - Medical, Dental and Vision insurance - Generous Parental Leave - Life Insurance and Disability benefits - $800/month remote work stipend And that's just the start — for more info check out our benefits and perks on our careers page. BELONGINGNESS AT PREFECT: Belongingness at Prefect is our commitment to ensuring mutual power, access, and opportunity among all groups and individuals who make up our community. We operationalize belongingness through actions large and small on a daily basis, but always with the goal that all groups and individuals can contribute as their most authentic self to the evolution of our product, our team, and our community. Belongingness is also our commitment to bridge with individuals or groups not yet established in our community, acknowledge differences in a way that affirms distinct identities, and allows for a new, more expansive group identity to form. EQUAL OPPORTUNITY AT PREFECT: Prefect is an equal opportunity employer and encourages applications from people of all backgrounds. All applicants will be considered for employment without attention to race, religion, color, sex (including pregnancy, sexual orientation and gender identity/expression), national origin, disability or any other status protected under applicable federal, state, or local laws. Delaney is a real live person (👋🏻) and is looking forward to learning more about you through your application.

Requirements

Must-haves

Our Vision: Prefect will define automation for the context era.
Our Mission: Curate an intelligent context layer that delivers the right information at the right time.
Own the go-to-market data model. One definition of an account. One definition of an activated workspace. One definition of pipeline. Version controlled, tested, documented, and deployed by you.
Model the self-serve funnel end to end, from first visit through signup, activation, paid conversion, and expansion, for both Prefect Cloud and Dagster+. Make the drop-off points visible and the cohorts comparable.
Model the sales funnel end to end, from source through MQL, SQL, pipeline, and closed won, including stage conversion and velocity, using Salesforce data as it actually is rather than as the schema claims.
Build attribution that marketing and sales both accept. First touch, last touch, and a multi-touch model, with the assumptions written down so the arguments are about strategy instead of arithmetic.
Build the unit economics. CAC and payback by channel and segment, LTV/CAC, ROI on campaigns and events, self-serve versus sales-assisted. That includes going and getting the spend data nobody has loaded yet.
Ship the reporting layer so go-to-market teammates answer their own questions instead of queuing behind you. We run two Omni instances, one per product. Looker experience transfers directly.
Help us set the go-to-market rhythm. Pipeline reviews, the weekly funnel meeting, board reporting. You'll hear a question before it becomes a ticket, and often you'll be the one who reframes it.
Four or more years building analytics models in dbt on a cloud warehouse, owned in production with tests, CI, and version control.
Strong SQL, plus enough Python for the parts SQL is bad at: API pulls, spend data, one-off enrichment.
Experience building and maintaining a semantic layer in Omni, Looker, or something comparable. We care that you have modeled metrics for other people to use, not that you have built dashboards.
Direct work with go-to-market teams on funnel conversion, attribution, and unit economics like CAC, payback, and ROI, using real CRM data from Salesforce or HubSpot.
Prior knowledge of GTM systems like Salesforce, Amplitude, Segment, Hubspot.
A product-led or self-serve business: activation, trial conversion, PQLs, usage-based revenue.
A background in engineering or data, meaning you write code, read other people's code, and deploy your own work.
Comfort with AI-native development.
You want to do machine learning or data science. There is plenty of interesting analysis here, but the core of the job is modeling and measurement for go-to-market decisions.
You want to take tickets. People will bring you questions like "why did self-serve conversion drop in August," not specifications. You decide what to measure.
You want to manage a team soon. This is an individual contributor role and will be for a while. You get a lot of influence over how go-to-market data works and no direct reports.
San Francisco Bay Area & NYC Metro: $173,000–$222,000
Washington D.C., Boston, LA Metro, Seattle: $162,000–$201,000

Nice-to-haves

Product analytics tools, especially Amplitude.
Developer tools or open source, where the funnel starts with a pip install and the top of it is a community rather than a lead list.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigosqlpythonapimachine learning

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Parental Leave