About the role

Aplyr's Quick Take

This role is for a Data Engineer who will design and manage data systems that support various business functions. You'll be responsible for building data pipelines, models, and dashboards, ensuring data quality and accessibility for decision-making. It's an individual contributor position focused on technical execution rather than team management.

Good fit

Ideal candidates have 4+ years in data engineering, are proficient in SQL, and have experience with tools like dbt or Airflow. A hands-on, detail-oriented approach and comfort with in-office work in San Francisco will help you thrive here.

Worth noting

The company requires in-office attendance five days a week, which may not suit remote work advocates. The role emphasizes a self-serve analytics culture, indicating a push for data democratization within the organization.

Factory is bringing autonomy to software engineering, and we’re hiring a Data Engineer to own the systems that power how we understand and operate the business. You’ll architect and evolve the full data stack, designing the pipelines, models, and integrations that turn raw information into reliable, real-time insight across product, engineering, finance, and GTM.

What you will do and achieve:

Build and refine the data models and warehouse architecture that serve as the backbone for product analytics, usage reporting, and business operations.
Design, operate, and scale the pipelines that move, transform, and validate data across internal and external systems.
Create the integrations that bring third-party and operational data into a unified, trusted environment.
Own the entire reporting surface at Factory, from core datasets and dashboards to the metrics leadership uses to steer the company.
Drive data quality, observability, governance, and documentation while helping teams adopt a self-serve analytics culture.

Qualifications

4+ years of experience in data engineering or a full-stack data role with deep expertise in SQL and strong proficiency in JavaScript or Python.
Hands-on experience with data modeling, warehouse architecture, and BI-oriented schema design, along with operational familiarity using tools like dbt, Airflow, or Dagster.
Experience supporting or building business intelligence environments.
Strong statistical intuition and experience running or supporting experimentation frameworks.
The team goes into the office 5 days a week in San Francisco (walking distance to Caltrain).

Skills & Tags

python java javascript go rust ai data analytics

Aplyr's read

Factory leverages AI to revolutionize manufacturing and supply chains, attracting tech-savvy professionals keen on transforming industrial processes.
Synthesized from recent postings & public sources

What's promising

•Factory's AI-driven solutions offer cutting-edge advancements in manufacturing efficiency.
•The company is expanding rapidly, hiring diverse roles across engineering, marketing, and operations.
•Factory's focus on supply chain optimization addresses critical industry challenges.

What to watch

•The niche focus on manufacturing may limit broader tech industry appeal.
•Rapid expansion could strain resources and affect workplace culture.
•Highly specialized technology may require steep learning curves for new hires.

Why Factory

•Factory integrates AI specifically for manufacturing, a less saturated tech niche.
•The company emphasizes solving complex supply chain issues with innovative technology.
•Factory's diverse hiring strategy supports a wide range of tech and business roles.

Aplyr’s read is generated by AI from public sources. Was it useful?