We're building a greenfield data platform and looking for an entry level Data Engineer to join our Automations team. This team sits at the intersection of data engineering and platform engineering - we own the DevOps, AI agent tooling, and test automation layer that makes the rest of the platform reliable and fast to iterate on. If you're early in your career and excited about building things the right way from day one, this is a rare opportunity to shape something from the ground up.

Core Responsibilities:
• Help design, build, and maintain CI/CD pipelines and infrastructure-as-code for a modern data platform
• Develop and maintain automated test suites to validate data pipelines, transformations, and platform components
• Contribute to AI agent workflows that automate operational and data tasks
• Collaborate with senior engineers to establish DevOps patterns and best practices on a greenfield codebase
• Monitor, debug, and improve platform reliability and observability
• Other duties as assigned.

Required Knowledge, Skills, and Abilities:
• Bachelor’s degree in computer science, Engineering, or a related field or equivalent practical experience
• Familiarity with Python and comfort writing scripts to automate tasks
• Basic understanding of data engineering concepts (pipelines, transformations, storage)
• Exposure to DevOps tooling such as Git, CI/CD systems (GitHub Actions, GitLab CI, etc.), or containerization (Docker, Kubernetes)
• Curiosity about AI/ML tooling and automation - prior experience is a plus, not a requirement
• Strong willingness to learn; experience with greenfield or 0-to-1 projects is a bonus

Desired Knowledge, Skills, and Abilities:
• Experience with a cloud platform (AWS, GCP, or Azure)
• Familiarity with data tools such as Databricks, Snowflake, Kafka, Spark, or similar
• Exposure to testing frameworks or quality engineering practices
• Any experience with LLM APIs or AI agent frameworks
• Minimum Required Education & Experience:
• Bachelor's degree in data or software engineering or a related field or equivalent.

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