Senior Software Engineer ll
Multi-Cell
Posted on 3/19/2024
INACTIVE
dbt Labs

201-500 employees

Empowers data practitioners with transformation framework and cloud-based
Company Overview
dbt Labs is a pioneering company in the field of analytics engineering, empowering data practitioners with a robust data transformation framework, dbt, used by over 20,000 companies for efficient analytics workflows. The company's cloud-based platform, dbt Cloud, supports over 3,000 customers, offering a centralized development experience that ensures safe deployment, monitoring, and investigation of code. With a focus on fostering a culture of collaboration and transparency, dbt Labs offers a scalable data management platform that promotes team unification, process standardization, and efficient onboarding of new data developers, while maintaining rigorous governance and control of analytics code.
Data & Analytics

Company Stage

Series D

Total Funding

$293.7M

Founded

2016

Headquarters

Philadelphia, Pennsylvania

Growth & Insights
Headcount

6 month growth

11%

1 year growth

1%

2 year growth

76%
Locations
Remote in USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Datadog
Kubernetes
Python
Postgres
Go
Terraform
Data Analysis
CategoriesNew
Backend Engineering
Full-Stack Engineering
Software QA & Testing
Software Engineering
Requirements
  • 7+ years experience in software engineering
  • Experience supporting SaaS applications
  • Bachelor's degree in related field or completed enrollment in engineering related bootcamp
  • Experience with Golang, Python, Postgres, Kubernetes, Terraform, Auth0, and Datadog
  • Experience in implementing large-scale distributed systems
  • Systematic problem-solving approach and strong communication skills
  • Experience with technical leadership (preferred)
Responsibilities
  • Build cell-based application architecture
  • Collaborate with engineering teams, Product Management, Security, and Customer Support
  • Work with a variety of programming languages, systems, and technologies
  • Drive scaling and automation initiatives
  • Define tradeoffs and make decisions about platform building
  • Ensure high programming standards
  • Participate in timely, constructive code review
  • Operate in a fast-paced environment
  • Drive progress in the data and analytics ecosystem