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Data Engineer – AI Data Platform. The Role: 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.
Job Responsibility:
Build and maintain reliable, production-grade data pipelines
Design scalable batch and real-time ingestion systems
Optimize performance and cost across Snowflake, ClickHouse, 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
Requirements:
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
Strong Python experience
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 ClickHouse
Strong ownership mindset with a focus on data quality and reliability