Yaroslav D.

I build customer-facing chatbots and the data systems behind them — so your automation is not a black box, but a measurable, improvable business asset. This profile combines three areas that naturally reinforce each other: - Chatbots generate high-volume conversation data and require reliable integrations. - Data engineering keeps knowledge bases and downstream datasets fresh and trustworthy. - Analytics turns chatbot + product/support data into clear KPIs, insights, and decisions. In practice, this means I can take you from "we want a chatbot" to "we know what it saves us, what users struggle with, and what to fix next." What I deliver 🤖 Chatbots - Scripted and AI-assisted chatbots for support, onboarding, lead qualification - Knowledge base structure + safe AI (RAG) where appropriate - Integrations via APIs/webhooks (CRM, ticketing, spreadsheets, databases) - Human handoff flows and conversation logging 💾 Data Engineering - API/data ingestion → PostgreSQL / BigQuery / ClickHouse - Scheduled syncs with retries, logs, monitoring, and idempotency (no duplicates) - Data cleanup, migrations, and reliable schemas - Pipelines to update chatbot knowledge bases and content sources 📊 Data Analytics - KPI dashboards (weekly/monthly views) in Looker Studio / Tableau / Grafana - Metric definitions and validation (single source of truth) - Funnel / drop-off analysis, trend detection, and actionable insights How I work 1. Quick audit: goals, current setup, constraints 2. Plan & milestones: deliverables + success metrics 3. Build + test: edge cases, monitoring, documentation 4. Handover: dashboards, runbook, next-step roadmap 🛠 Technology stack I work with: - Languages: JavaScript/Node.js, Python, SQL - Databases/Warehouses: PostgreSQL, BigQuery, ClickHouse - BI: Looker Studio, Tableau, Grafana - Automation: Make, Zapier, n8n - Chatbot platforms: Botpress, Chatfuel, ManyChat, SendPulse (and custom builds when needed) Notes - I don’t work with Russia/Belarus-based businesses. - No gambling projects.