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Data Engineer, Analytics

Location
San Francisco
Compensation
Not disclosed
Level
mid
Type
full time

Skills & Technologies

Requirements

Experience
4+ years

Joblaze summary

In this role, the Analytics Engineer at Cursor will engage directly with various teams to understand their data requirements and develop foundational datasets that drive strategic decisions. Proficiency in SQL and Python is essential, along with experience in optimizing large-scale data queries and familiarity with modern data stacks. This position is ideal for someone with at least four years of analytics engineering experience, particularly in a fast-paced startup environment. As an early member of the data team, the engineer will play a crucial role in establishing a self-serve data culture.

Joblaze insights

Quick facts

How much experience is required?
At least 4 years of relevant experience for this Data Engineer, Analytics role.
What's the tech stack?
Joblaze extracted these technologies from the posting: dbt, SQL, Python.
What seniority level is this role?
Cursor targets mid-level candidates for this position.
Is this full-time or contract?
Full-time for this Data Engineer, Analytics role at Cursor.

From the original posting

Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.

About the Role

As one of Cursor’s first Analytics Engineers, you’ll work hands-on across the entire stack to build data products and drive strategic decisions across product, GTM, and research. You'll partner directly with founders and area leads on critical questions, collaborating with uniquely data-savvy stakeholders who are eager to jump into SQL and dbt. Through this collaboration, you’ll pioneer the next frontier of data: defining how Cursor itself transforms data science by building a data stack around Cursor Agent for self-serve analytics.

What you’ll do

  • Partner with area leads in Finance, Growth, Product, and Agent Quality to understand their data needs and build foundational datasets.

  • Up-level our data stack by evaluating new tooling and AI integrations, while partnering with Data Infra and product engineers to maximize the impact of existing tooling.

  • Ensure the quality and reliability of data in our warehouse.

  • Help guide a vibrant self-serve data culture to make self-serve insights accessible and trustworthy.

  • Establish data culture and foundations as an early member of the data team and our first analytics engineer.

You may be a fit if

  • You have at least 4+ years of full-time analytics engineering experience.

  • You’ve been an early data member at a hyper-growth startup or research org. You know how to scale data from 10 to 50 data scientists.

  • You’ve optimized queries for speed and cost on datasets that grow by billions of rows per day.

  • You can write SQL and Python in your sleep.

  • You care deeply about accuracy and detail.

  • You’re excited about the modern data stack and self-serve data.

  • You’re excited to build data products end to end, even if it requires going outside the original job description.

  • #LI-DNI

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