Data Engineer

Cognition

📍San Francisco, CA
Posted May 18, 2026

Job Overview

Position

Data Engineer

Company

Cognition

Location

San Francisco, CA

Work Type

On-site

Job ID

li-4347907138

Job Description

We are an applied AI lab building end-to-end software agents.
We're the makers of Devin, the first AI software engineer, and Windsurf, the AI-native IDE. Together, they represent our vision for collaborative AI teammates that enable engineers to focus on more interesting problems and empower teams to strive for more ambitious goals.

Our team is small and talent-dense. Among our founding team, we have world-class competitive programmers, former founders, and leaders from companies at the cutting edge of AI including Scale AI, Palantir, Cursor, Waymo, Tesla, Lunchclub, Modal, Google DeepMind, and Nuro.

Building Devin and Windsurf is just the first step—our hardest challenges still lie ahead. If you’re excited to solve some of the world’s biggest problems and build AI that can reason on real-world tasks, apply to join us.

About The Role
We're hiring a technical Data Engineer to own our full data stack – from database architecture and pipelines to instrumenting telemetry and owning integrations and reporting. You'll design and maintain the systems that keep our data reliable, accessible, and actionable across the company.
*There are multiple openings across various teams: GTM, Core Product, and Finance.*
In This Role You Will

  • Design and manage database architecture and data models

  • Build and maintain ETL/ELT pipelines and orchestration workflows

  • Create and manage new data integrations across internal and external systems

  • Own business reporting: datasets, dashboards, metrics, and self-serve analytics

  • Ensure data quality, observability, governance, and documentation

Requirements For The Role

  • 4+ years in a data engineering, data science, or full-stack data role

  • Expert on SQL and Python (required)

  • Experience with data modeling, warehouse architecture, and BI-oriented schema design

  • Hands-on experience with ETL/ELT tools (dbt, Airflow, Dagster, etc.)

  • Experience building or maintaining BI reporting (Metabase a plus)

  • Experience developing scalable backend heavy applications

  • Strong knowledge of statistics and experimentation

  • Based in SF or NYC

Equal Opportunity

Cognition is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law. We are committed to providing reasonable accommodations for candidates with disabilities throughout the hiring process - please let us know if you need any.

Interview Prep

AI-powered insights to help you prepare

Key Skills

Required:
Preferred:

Practice Questions

💡Technical Questions (3)
  • 1.How would you design a data warehouse architecture and schema to handle high-volume telemetry data from an AI-native IDE like Windsurf, ensuring it remains performant for both GTM and Core Product teams?
  • 2.Can you walk me through how you would use dbt and an orchestrator like Airflow or Dagster to build an ELT pipeline that transforms raw product usage data into actionable metrics for business reporting?
  • 3.Given the requirement for strong knowledge of statistics and experimentation, how would you design the data infrastructure to support A/B testing for new features in an AI software agent like Devin?
🎯Behavioral Questions (3)
  • 1.Tell me about a time you had to own the full data stack—from database architecture to business reporting—for a complex project. How did you ensure the data remained reliable and actionable?
  • 2.Describe a situation where you had to build a new data integration with an external or internal system that had poor or undocumented APIs. How did you handle it?
  • 3.At Cognition, we are a small, talent-dense team. Tell me about a time you worked in a high-paced, elite environment where you had to ramp up quickly on a new technology or domain to deliver results.
🧩Situational Questions (2)
  • 1.You are the Data Engineer for the Core Product team. Product managers complain that the daily active user (DAU) metrics on the dashboard look off by 20% compared to last week, but the underlying telemetry pipelines show no failures. What is your approach to debug and resolve this?
  • 2.The Finance team needs a new dashboard to track cloud compute costs for Devin's AI workloads, but the data is currently scattered across multiple cloud provider APIs and internal billing systems. How would you approach this from architecture to reporting?

Resume Keywords

Make sure these keywords appear on your resume

Data EngineerPythonSQLdbtAirflowDagsterETL/ELTData ModelingData WarehouseTelemetryBI ReportingExperimentation

Interested in this position? Apply directly on LinkedIn.

Apply on LinkedIn →