Data Engineer, Finance

Reposted 11 Days Ago
San Francisco, CA, USA
In-Office
5-5 Annually
Senior level
Artificial Intelligence • Software
The Role
As a Data Engineer, you will design database architecture, manage ETL/ELT pipelines, create financial reporting systems, and ensure data quality in collaboration with finance teams.
Summary Generated by Built In
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 Data Engineer to help own our data stack — from database architecture and pipelines to integrations and reporting. You’ll design and maintain the systems that keep our data reliable, accessible, and actionable across the Finance and Accounting organization.

In this role you will:

  • Design and manage database architecture and data models with a focus on finance and accounting use cases

  • Build and maintain ETL/ELT pipelines and orchestration workflows

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

  • Partner with Finance and Accounting teams to build auditable, automated reporting systems, dashboards, and datasets

  • Support close processes, FP&A workflows, and revenue reporting through scalable data infrastructure

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

  • Ensure data quality, observability, governance, and documentation

Requirements for the role:

  • 5+ years in a data engineering, analytics engineering, or a full-stack data role

  • Expert SQL and strong Python (or R)

  • 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)

  • Proven track record collaborating with finance stakeholders to deliver impactful solutions

  • Experience with FP&A processes, close workflows, and financial reporting

  • Familiarity with GAAP vs. non-GAAP reporting and revenue recognition concepts

  • Based in SF and willing to be in office 5 days a week

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.

Skills Required

  • 5+ years in a data engineering, analytics engineering, or a full-stack data role
  • Expert SQL and strong Python (or R)
  • 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)
  • Proven track record collaborating with finance stakeholders to deliver impactful solutions
  • Experience with FP&A processes, close workflows, and financial reporting
  • Familiarity with GAAP vs. non-GAAP reporting and revenue recognition concepts
Am I A Good Fit?
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The Company
49 Employees

What We Do

Makers of Devin, the first AI software engineer. We are an applied AI lab building end-to-end software agents. We’re building collaborative AI teammates that enable engineers to focus on more interesting problems and empower engineering teams to strive for more ambitious goals.

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