Jobs Companies Prefect Staff Data Engineer

À propos de ce poste Staff Data Engineer chez Prefect

Prefect · Télétravail · Remote

Prefect builds and operates resilient, Pythonic orchestration and MCP platforms -- Prefect OSS, Prefect Cloud, FastMCP OSS, and Horizon -- 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

Prefect and Dagster merged in 2026, and we're consolidating two data stacks onto one: Snowflake as the warehouse, Dagster as the orchestrator, dogfooded on our own product. You'll take over our existing internal data platform, land the migrated stack at cutover, and own it end to end from there. You own finding and deciding requirements, setting the roadmap, and working directly with stakeholders across orgs. Part of our platform is open source (dagster-open-platform) and your work is a public reference implementation of our own product. You’ll report to Jenny, our Head of Engineering.

What You'll Do

  • Own the internal data platform end to end: Snowflake architecture, sizing, and cost; dbt transformations; orchestration standards in Dagster

  • Own ingestion tooling (Fivetran, Sling, dlt, AWS DMS) and reverse ETL (Hightouch, Census)

  • Own warehouse access controls and security — increasingly important as MCPs touch more of our data

  • Design the system so teams stop blocking each other: fewer cross-team dependencies, less homegrown ingestion debt, a sane change-data-capture story

  • Own platform reliability: Dagster+ alerting, data quality, and cost

  • Take on the deferred data backlog: one-off ingestion, enablement, and growth data work

  • Partner with engineering on SLA-carrying pipelines (billing, consumption pricing) where engineering retains ownership

  • Live in Dagster daily and feed what you learn back to the product team

Your Qualifications

  • Staff-level data platform experience - you set architecture across orgs and work through stakeholders independently

  • Deep production experience with dbt and a modern cloud warehouse

  • Experience with a modern orchestrator and experience with Dagster is a plus

  • Hands-on with managed ingestion and reverse ETL tooling

  • Self-directed and able to turn ambiguous business asks into scoped, prioritized work

  • Comfortable working in the open on a public codebase

What You'll Get in Return:

Base Salary Ranges :

  • San Francisco Bay Area & NYC Metro: $221,000-$276,000

  • Washington D.C., Boston, LA Metro, Seattle: $200,000-$257,000

  • Denver, Chicago, Atlanta, & all other U.S. metros: $191,000-$238,000

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.

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Comment se compare ce salaire pour Data Engineer

Ce poste paie $233,500/yrau-dessus de la fourchette habituelle pour les postes Data Engineer.

$109,800 la médiane $165,000 $239,580

Fourchette typique $132,841–$197,000/yr, à partir de 273 annonces Data Engineer comparables sur JobsRadar (rémunération annualisée en USD). Voir les aperçus de salaire pour Data Engineer →

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