Data Engineer

A bit about the role:

Cantina is building a groundbreaking AI-powered social platform where users create hyper-realistic AI characters that can talk, think, and interact across group chats, video, and voice. To make that magic happen, we rely on a robust and flexible data infrastructure—especially when data lives outside traditional warehouses.

As a Data Engineer on the Cantina Labs team, you'll work on ingesting and processing high-volume data streams directly from backend systems and services—not just from the warehouse. You’ll play a critical role in building reliable pipelines and data products that power insights, product features, and real-time systems.

This is a mid-level role (1–3 years of experience) that’s ideal for someone who’s excited to work at the intersection of infrastructure, real-time data, and platform scalability.

A bit about the work:

• Build and maintain scalable data pipelines that ingest data from backend systems and services, including Kafka-based event streams

• Work closely with engineering and product teams to understand data needs and design integrations

• Ensure data quality, availability, and reliability across batch and streaming environments

• Collaborate on data modeling, tooling, and frameworks for analytics, experimentation, and ML pipelines

• Improve performance and cost-efficiency of existing systems and pipelines

• Help define best practices around monitoring, alerting, data testing, and observability
  

A bit about you:

• 1–3 years of experience in data engineering or software engineering focused on data-intensive systems

• Experience with Kafka or other event streaming platforms (e.g., Pulsar, Kinesis)

• Proficiency with Python, SQL, and tools like Airflow, dbt, or similar

• Experience working with cloud infrastructure (preferably AWS or GCP)

• Comfort navigating unstructured data and distributed systems

• Strong communication and collaboration skills—this is a cross-functional role
  

Bonus Points For

• Experience with real-time data processing frameworks (e.g., Flink, Spark Streaming)

• Familiarity with backend services, microservices architecture, or observability stacks

• Exposure to ML data pipelines or experimentation frameworks
  

Location

This is a hybrid role, preferably based in the San Francisco Bay Area.

Pay Equity:

In compliance with Pay Transparency Laws, the base salary range for this role is between $160,000-220,000 for those located in San Francisco and Los Angeles, CA. When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.