Data Engineer

We’re partnering with a fast-growing AI startup building the analytics and observability layer for AI search - essentially “Google Analytics for LLMs.”

As more users discover products through tools like ChatGPT, Claude, and Perplexity, companies lack visibility into how they appear in those responses. This platform solves that - and the data challenges are significant.

They’re hiring a Data Engineer to help scale the core data infrastructure powering this system - handling large-scale, real-time data and enabling analytics, experimentation, and ML-driven insights.

• Build and maintain reliable, production-grade data pipelines
• Design scalable batch and real-time ingestion systems
• Optimize performance and cost across Snowflake, Click House, AWS, dbt, and Dagster
• Own data quality, validation, and monitoring end-to-end
• Develop and maintain transformation logic powering analytics and product features
• Support ML workflows (MLOps) with clean, structured, high-quality data
• Work closely with product, data, and engineering teams

• Proven experience building and maintaining production data pipelines
• Strong SQL skills (must-have)
• You’ve written complex queries, optimized performance, and worked deeply with analytical datasets
• Comfortable modeling data and transforming large datasets efficiently
• Hands-on experience with:
• dbt
• Orchestration tools (Dagster, Airflow, or Prefect)
• AWS (or similar cloud environments)
• Experience with modern data warehouses such as Snowflake or Click House
• Strong ownership mindset with a focus on data quality and reliability
• Interest in or exposure to ML pipelines / MLOps

• Work with data powering enterprise-scale AI products
• Company has:
  Grown rapidly to ~$30M AR, Raised $96M Series C at ~$1B valuation
• Solve real problems across:
  Real-time data pipelines, AI-driven analytics, ML infrastructure

• High ownership - real impact on platform design
• Early-stage but already scaled - strong product-market fit
• Work at the intersection of AI, data, and user behaviour
• Competitive compensation + meaningful equity

If you’re excited to work on high-scale data systems powering real-world AI applications, we’d encourage you to apply.