Enterprise AnalyticsRole: Product Analyst2025

AI-Powered Chat with Data Analytics Platform

Conversational analytics platform translating natural language questions into SQL executed against a ClickHouse data warehouse.

PythonSQLClickHouseAWSAI APIs

At a Glance

Role & Scope
Product Analyst — Design through production deployment
Core Stack
Python, SQL, ClickHouse, AWS, AI APIs
Project Type
Internal Data Product / Conversational Analytics
Business Area
Self-serve Product & Engagement Analytics
01

Overview

Built at Coffer Internet Service (PowerPlay), this platform enables non-technical team members and business stakeholders to query large analytical event logs using natural language. It translates conversational questions into validated SQL, queries a ClickHouse columnar warehouse, and returns structured data tables and charts without requiring manual analyst intervention.

05

What I Worked On

  • Designed the end-to-end query translation pipeline: conversational input → validated SQL syntax → ClickHouse execution → structured response payload.
  • Integrated AI APIs for query intent classification, parameter extraction, and database schema matching.
  • Optimized ClickHouse analytical queries across event datasets to keep query response times suitable for interactive conversational usage.
  • Collaborated with product managers and business stakeholders to define standard reporting metrics and common self-serve analytics workflows.
  • Automated reporting flows, reducing ad-hoc reporting requests by approximately 40% based on internal team tracking.
08

Key Takeaways

  • Demonstrates end-to-end ownership of an internal data product from requirement gathering to production adoption.
  • Combines conversational AI interfaces with columnar data warehouse performance.
  • Bridges technical data infrastructure with non-technical stakeholder decision workflows.
10