Data Ops

Canopy Labs; San Francisco (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

Canopy Labs is seeking a data operations leader to own the end-to-end data pipeline, from sourcing and negotiating large-scale data contracts to building operational processes that deliver data quickly to the research team.

You will work at the intersection of researchers, data providers, and customers, with a high degree of autonomy to design scalable data operations at a fast-growing company.

Qualifications

• Experience negotiating large data licensing and data acquisition contracts.
• Experience designing and optimizing data pipelines and workflows.
• Ability to coordinate across research, engineering and external partners.

Responsibilities

• Negotiate and manage large data licensing and acquisition contracts.
• Design and run operational workflows that move data from source to training pipeline.
• Build lightweight internal tooling and automation to scale data operations.
• Coordinate across research, engineering, and external partners to unblock model development.
• Support data capture sessions involving actors and directors.

Skills

Data negotiation

Contract management

Data pipeline design

Cross-functional collaboration

Project management

Education

STEM degree

Job description

Salary $120k+ base with performance based bonus

Data is the lifeblood of our models. In this role you will own the end-to-end data pipeline — sourcing, negotiating, and closing large-scale data contracts, then building the operational processes to get that data to the research team quickly and reliably. You will sit at the intersection of the research team, third-party data providers, and customers.

Why you may want to join

• Own a critical function — the quality of our data directly determines the quality of our models
• Unusual mix of negotiation, operations, and technical work rarely found in one role
• Work with actors, directors, and creative professionals alongside a world-class research team
• High autonomy to design processes from scratch at a fast-growing company

What you will do

• Negotiate and manage large data licensing and acquisition contracts
• Design and run operational workflows that move data from source to training pipeline
• Build lightweight internal tooling and automation to scale data operations
• Coordinate across research, engineering, and external partners to unblock model development
• Run processes for actors and directors involved in data capture sessions

Typical backgrounds

• Top STEM programs
• Investment banking or private equity
• Management consulting (e.g. McKinsey, BCG, Bain)
• Operations roles at high-growth startups

What is the interview process?

Step 1: Introduction Call

• Assess your fit from a skill perspective
• Assess your fit from a culture perspective
• Give you a chance to ask questions and find out more

You will spend time with the team in person, learning about the problems we face across data sourcing, pipeline operations, and partner coordination. You will share your own insights, discuss challenges, and work through real scenarios together.

Step 3: On-site

You will spend 2–5 days in person with the data ops team. Depending on the situation you would either work through an operational challenge the team has already tackled, take on a new data pipeline or vendor coordination problem with the team, or another activity that seems productive with two aims:

• Helping the data ops team get a sense of working with you
• Helping you get a sense of working with the data ops team