Data Engineer

Backed by Lightspeed, Y Combinator, Together Fund, and Prosus, Emergent is reimagining how software gets built. 

Our vision is to democratize development, enabling anyone with an idea to become a creator and making software accessible to a billion people worldwide. Our autonomous coding agents turn plain-language ideas into fully functional applications, tested, version-controlled, and deployable in minutes. What once took weeks now happens with a single click. 

Headquartered in San Francisco, we’re led by repeat entrepreneurs with a proven track record of building successful startups, joined by a world-class team of Olympiad medalists, IIT & IIM alumni, and veterans from Google, Amazon, and Dropbox. Together, we’re building at the frontier of AI and systems engineering, shipping daily and setting new standards for AI-driven development. 

In just 5 months, we scaled to $25M ARR, shipped 3M+ Apps, with 2.5M users across 180+ countries, making us one of the fastest-growing AI startups in the world. 

Join us in shaping the future of software development.

What You’ll Do 

• Design, build, and maintain robust, scalable data pipelines and infrastructure. 
• Develop ETL/ELT processes to collect, process, and curate structured and unstructured data from various sources.
• Collaborate with data scientists, analysts, and product teams to understand data needs and ensure data reliability and accessibility. 
• Optimize data systems for performance, cost-efficiency, and scalability. 
•  Ensure data quality, security, and compliance best practices are followed.
• Implement and maintain data models, data lakes, warehouses (e.g., Redshift, BigQuery, Snowflake), and real-time streaming platforms (e.g., Kafka, Spark). 
• Document systems and contribute to internal data engineering standards and playbooks.
  
  

What We’re Looking For 

• 3+ years of experience in a data engineering or similar backend role. 
• Proficiency in Python, SQL, and one or more data orchestration tools (e.g., Airflow, Dagster, Prefect).
• Hands-on experience with cloud data platforms (AWS, GCP, or Azure). 
• Familiarity with data modeling, warehousing concepts, and distributed systems.
• Strong understanding of data governance, privacy, and security principles. 
• Experience with tools like dbt, Kafka, Spark, or similar technologies is a plus. 
• Bonus: Background in ML pipelines, MLOps, or DevOps practices.

Why Join Us?

This isn't a traditional analyst position. You'll be pioneering analytics in the emerging field of agentic AI, where your work directly shapes how we understand and optimize AI agent

performance. You'll have the opportunity to:

• Be among the first analysts to define metrics and frameworks for agentic AI systems
• Work with cutting-edge technology while solving novel analytical challenges
• Have direct impact on product decisions with your insights driving feature development
• Shape the future of how businesses measure and optimize AI agent effectiveness

Let’s build the future of software together.