Data Engineer

Cantina Labs • Full-time • San Francisco, CA, US • $160k - $220k / year • 17h ago

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 (3-6 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

3+ years of experience in data engineering or software engineering focused on data-intensive systems
Computer Science or related degree (i.e. Applied Math, Statistics, Econometrics, Computational Biology, Bioinformatics)
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, in-person 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.