Data Pipeline Engineer / ML Infrastructure Engineer (Remote, NYC, Austin)

Posted:
10/9/2024, 6:14:34 PM

Location(s):
New York, United States ⋅ Texas, United States ⋅ New York, New York, United States ⋅ Austin, Texas, United States

Experience Level(s):
Mid Level ⋅ Senior

Field(s):
AI & Machine Learning ⋅ DevOps & Infrastructure

Workplace Type:
Remote

At Trunk Tools, we are tackling the massive $13 trillion+ construction industry. We’re an exceptional team of serial entrepreneurs, brought together by our shared mission: automating construction. Our founding team (SpaceX, Stanford, MIT, Carta, etc.) has successfully built and deployed software in construction for 140k+ users, millions of users beyond the construction space, and worked on +$2 billion of built-environment projects. We aren’t another out-of-touch tech startup, most of our team comes from construction. 

We spent the last few years building the brain behind construction. Now we are deploying workflows/ agents, starting with Q&A document chatbot, to be ingrained in construction teams’ workflows, ultimately to automate construction. Given our immense traction with several Fortune 500 construction companies,  we are doubling our team in order to deploy several more agents this year. You will have an opportunity to drive the transformation of a multi-trillion-dollar industry full of waste, risks and inefficiencies.

What you will do and achieve:

  • Design, develop and maintain robust file processing pipeline infrastructure

  • Orchestrate the flow of data through various stages of processing

  • Ensure observability and monitoring of the pipeline’s health

  • Integrate data from various sources including industry storage platforms, project management tools, and external APIs

  • Implement data quality checks and error handling mechanisms to ensure data integrity

  • Collaborate with the machine learning team to enhance pipeline functionality and efficiency

Who you are:

  • BS/MS in Computer Science, Information Systems, or a related field

  • 5+ years of experience in ETL development and data engineering

  • Strong coding proficiency in Python and database systems (SQL, noSQL)

  • ​​Strong experience with pipeline orchestration tools (eg. Prefect), infrastructure-as-code (eg. Terraform), and observability and monitoring tools

  • Understanding of serverless architectures (eg. AWS Lambda)

  • Familiarity with ML workflows and requirements (to effectively collaborate with the ML team)

  • Knowledge of data modeling and data warehouse concepts

  • Interest in the construction industry

If you're passionate about building robust data pipelines that will power the future of construction automation, we want to hear from you!

What we offer 😎

🎖️ A close-knit and collaborative early-stage startup environment where every voice is heard and every opinion matters; currently, we're 30 team members.

💰 Competitive salary and stock option equity packages.

🏥 3 Medical Plans to choose from including 100% covered option. Plus Dental and Vision Insurance!

💰 401K

🤓 Learning & Growth stipend.

🥨 Free lunch provided in NYC and Austin office - you’ll never go hungry with us!

🛫 Unlimited PTO; We truly believe in work-life balance and that hard work should be balanced with time for rest and rejuvenation.

🏝 IRL / In-Person retreats throughout the year.

We realize applying for jobs can feel daunting at times. We don’t expect you to check all the qualification boxes and encourage you to apply if you have experience in some of the areas.

At Trunk Tools, we’re working hard to build a more productive and safer environment within the construction industry, and we strive to live by these same values here at Trunk Tools HQ. As an equal-opportunity employer, we are committed to building an inclusive environment where you can be you. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, pregnancy, gender expression or identity, sexual orientation, or any other legally protected class.