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Senior Data Engineer

Senior Data Engineer

CantinaSan Francisco, CA, United States
3 days ago
Job type
  • Full-time
Job description

A bit about Cantina :

Cantina, founded by Sean Parker, is a new social platform with the most advanced AI character creator. Build, share, and interact with AI bots and your friends directly in the Cantina or across the internet.

Cantina bots are lifelike, social creatures, capable of interacting wherever humans go on the internet. Recreate yourself using powerful AI, imagine someone new, or choose from thousands of existing characters. Bots are a new media type that offer a way for creators to share infinitely scalable and personalized content experiences combined with seamless group chat across voice, video, and text.

If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!

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.

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 :

  • 5+ 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.

    Benefits :

  • Health Care - 99% of premiums for medical, vision, dental are fully paid for by Cantina, plus One Medical membership.
  • Monthly Wellness Stipend - $500 / month to use on whatever you'd like!
  • Rest and Recharge - 15 PTO days per year, 10 sick days, all Federal holidays, and 2 floating holidays.
  • 401(K) - Eligible to participate on day one of employment.
  • Parental Leave & Fertility Support
  • Competitive Salary & Equity
  • Lunch and snacks provided for in-office employees.
  • WFH equipment provided for full-time hybrid / remote employees.
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