Cognition

Cognition

Data Engineer

San Francisco

Sponsorship not specifiedDetected 325 days ago
PythonFull-Stack DevelopmentSQLAirflowdbtData EngineeringData ScienceStatisticsA/B TestingMetabase

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odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • There are multiple openings across various teams: GTM, Core Product, and Finance.
  • 4+ years in a data engineering, data science, or full-stack data role

Responsibilities

  • Build and maintain ETL/ELT pipelines and orchestration workflows
  • Create and manage new data integrations across internal and external systems
  • Building Devin 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.
  • You'll design and maintain the systems that keep our data reliable, accessible, and actionable across the company.
  • Own business reporting: datasets, dashboards, metrics, and self-serve analytics

Requirements

  • 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.)
  • Strong knowledge of statistics and experimentation

Skills

  • Design and manage database architecture and data models

Company info

  • We are committed to providing reasonable accommodations for candidates with disabilities throughout the hiring process - please let us know if you need any.
  • WE ARE AN APPLIED AI LAB BUILDING END-TO-END SOFTWARE AGENTS.

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.
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This listing is sourced directly from Cognition's careers page and normalized into a canonical job model.