Data Engineer

Role overview Build the data pipelines and models that turn AI agent conversations into dependable analytics about sessions, requests, and outcomes. You’ll shape event definitions, transform raw activity into queryable tables, and help teams understand conversion and errors while guarding against common data quality problems.

Responsibilities - Design event schemas for agent conversations and their outcomes. - Build pipelines that transform raw events into analytics tables. - Calculate product measures such as request conversion and session error rates. - Make data processing resilient to reloads, duplicates, and missing fields. - Document data models so they are easy for others to query.

Requirements - Strong SQL and Python skills. - Experience with data pipelines, orchestration, and a modern data warehouse. - Understanding of event tracking and data quality checks. - Careful handling and validation of metrics. - Relevant experience may include data or analytics engineering, product analytics infrastructure, or backend engineering with substantial data work.

Benefits and work setup Remote contract with flexible hours. Compensation starts at $4,500 per month. Freelancers and solo agencies may continue working with their own clients. The selection exercise involves generating conversations with varied outcomes, building session and request tables, labeling synthetic events, calculating conversion and error measures, and checking repeated loads and missing required fields. There is no time limit.