Data Engineer

Workos·United States & CanadaRemotemid$14,583–$20,000 USD/mo

In short

→Ingeniero de Datos que gestiona todo el flujo de datos interno: ingestión, transformación en Snowflake, modelos dbt y acceso seguro.
→Dia a dia: construir pipelines, definir métricas con equipos, mantener la confiabilidad y escalar el sistema con ayuda de agentes de IA.
→Destacado: trabajan con un sistema operativo 'agent-first', donde IA y humanos colaboran en el código, pruebas y ejecución.

No se requiere inglés.

In ~1 minute you get: who interviews you, the likely questions answered from your CV, and your CV tailored to this job. Free, no card.

🎧Land the interview? Bring the copilot. Our free extension listens to the live interview and flashes 3-4-word anchors from your resume and prep — glance, connect, talk. Get the extension →

What they ask for

✓Experiencia con Snowflake y dbt para modelos de datos (Bronze/Silver/Gold)
✓Capacidad para diseñar y mantener pipelines de ingesta y orquestación escalables
✓Trabajo colaborativo con equipos de producto, finanzas y comercial
✓Habilidades para diagnosticar discrepancias en métricas y rastrear errores desde dashboard hasta origen
✓Interés en aplicar IA en la operación de datos (agentes que ejecutan runbooks, PRs, etc.)
✓Enfoque proactivo: automatizar tareas repetitivas, documentar, trabajar en público.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

SnowflakedbtAirflowGitHubSlackSalesforceJiraGA4PosthogFlashboards

Who should you write to at Workos?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

Compensation: $175K – $240K. About WorkOS 🚀 WorkOS builds modern developer tools and APIs that make it easy for companies to become Enterprise Ready. Our platform powers authentication, identity, authorization, and other critical infrastructure that developers need to securely scale their products to large organizations. We recently raised a $100M Series C, valuing the company at $2B, led by Meritech and Sapphire with participation from Greenoaks, Craft, Abstract, and Audacious. WorkOS powers enterprise features for many of the fastest-growing AI companies, including OpenAI, Cursor, and Perplexity, Sierra, and Plaid. As AI reshapes software, WorkOS is at the frontier of Human and Agent Authentication, Identity, and Access Control helping companies answer a new critical question: who are your agents, and what are they allowed to do? Our fast-growing customer base includes hundreds of modern software companies building the next generation of enterprise-ready products. ABOUT THE ROLE The Data team at WorkOS plays a central role on the company operations to ensure information and insights are accurate and available from any surface, whether that's a visualization tool or an agent's response, to accelerate company growth and scale. The team owns WorkOS's internal data platform end to end: ingestion, orchestration, the Snowflake warehouse, dbt transformations, governance and access controls. We also own the consumption layer: the reverse-ETL syncs that land data in Salesforce and Slack, the semantic views that agents query, the definitions that keep reporting consistent across the company, and the visualization tooling the company uses (ask us about Flashboards https://workos.com/blog/reporting-tool-with-no-editor). We run on an agent-first operating system: we are a lean team that moves fast, we document so agents can execute, and AI agents query the warehouse, run our runbooks, and open pull requests alongside us. We trust each other's expertise, we work out loud and in the open, and not opposed to rapid experimentation to get to the right solution for the business. We're hiring a Data Engineer to own and evolve the systems that move, transform, protect, and serve data across our internal warehouse. This is a high-ownership role on a lean team: you will be the DRI for the platform and its core data models, partner directly with Product Engineering, RevOps, Finance, GTM Engineering, and Security, and raise the bar on reliability, correctness, and operational rigor. The role spans the platform and what runs on it. You will own ingestion, orchestration, and access governance; the dbt models and metric definitions that depend on them; and how AI is applied across the data stack, so that trusted data is easy for both people and AI agents to discover, understand, and work with. You don't need to have done this exact job before. The best data engineers at WorkOS are the ones who notice in a Slack thread that a number doesn't match, trace it from the dashboard through the Gold model to the connector, fix the connector, and confirm the definition with its owner before the weekly review. When a business team asks for a field in Salesforce, they don't hand it off; they build the model, write the sync, and add the test. They would rather automate the runbook than run it a third time. They enjoy collaboration with different parts of the business and can find simple, scalable solutions to ambiguous problems. If that sounds like how you work, we want to talk. RESPONSIBILITIES - Own the reliability, freshness, and scaling of the ingestion and orchestration pipelines that land source data in Snowflake, including monitoring, alerting, runbooks, and backfill and reprocessing patterns - Design, build, and scale the core dbt models (Bronze, Silver, Gold) for billing and usage, CRM, product events, and GTM funnel reporting - Partner with Product, Finance, RevOps, and GTM to define metrics and codify them in the warehouse, and diagn

Looking for something similar?

Leave your email and we'll alert you when matching jobs appear.

Don't apply unprepared

We research who's interviewing you, tailor your CV and rehearse you live — first one free.