Senior Python Data Engineer & AI Business Intelligence Platform Developer — B2B Market Intelligence,

# Job Title **Senior Python Data Engineer & AI Business Intelligence Platform Developer — B2B Market Intelligence, Data Pipelines & AI** ## About Our Business Vidya Timber is a family-owned plywood, timber and interior materials business based in Varanasi, India. We are expanding into modular interiors and developing our premium architectural door brand, Archwood. We are looking to build an AI-powered B2B Market Intelligence Platform that helps our sales team discover potential customers, identify construction projects, understand business relationships and prioritize high-value commercial opportunities. We are looking for an experienced technical professional who can build a reliable, scalable and production-ready platform—not just a prototype, chatbot or basic lead-generation tool. ## Project Vision The platform should help us identify: - Architects and architecture firms - Interior designers - Builders and real estate developers - Contractors and construction companies - Plywood, timber and building-material dealers - Publicly announced construction and real estate projects The long-term objective is to transform publicly available business intelligence into actionable sales opportunities for Vidya Timber and Archwood. ## Core Responsibilities ### 1. B2B Business Intelligence Data Collection - Develop reliable data pipelines using Python. - Collect publicly available business information from relevant sources. - Explore sources such as Google Maps, company websites, project portfolios, public RERA records, government project announcements, news publications and business directories. - Discover construction projects in Varanasi and Uttar Pradesh, including projects not yet listed on RERA. - Maintain source URLs, discovery dates and verification status for collected records. - Implement deduplication, data cleaning and enrichment workflows. - Respect website terms, applicable laws, privacy requirements and data access restrictions. ### 2. Database & Data Engineering - Design a structured PostgreSQL database. - Build relationships between companies, people, projects and business activities. - Implement data validation and quality checks. - Maintain a reliable data ingestion and update process. - Design the system for future expansion across multiple cities and states. ### 3. AI-Powered Intelligence - Use LLMs for extracting structured information from public sources. - Implement AI-assisted company enrichment and opportunity identification. - Develop transparent lead scoring based on business relevance and evidence. - Generate actionable reports explaining why a prospect is valuable. - Explore RAG, GraphRAG and AI agents where they provide measurable value. **Important:** We do not want unnecessary AI complexity. The developer should recommend the right architecture based on actual business requirements. ### 4. Working Business Intelligence Dashboard Develop a functional web application that allows our sales team to: - Search and filter prospects. - View company profiles and associated projects. - Understand relationships between architects, builders and contractors. - View lead scores with explanations. - See original source references. - Record calls, follow-ups, notes and sales outcomes. - Export prospect data to CSV or Excel. - Identify the next recommended sales action. ### 5. AI Agents & Future Integrations The platform should eventually support: - Scheduled intelligence collection. - AI-assisted research workflows. - CRM integrations. - Sales reporting. - MCP server integrations where useful. - Automated business opportunity alerts. ## Preferred Technical Skills **Essential:** - Python - PostgreSQL - Data engineering and ETL pipelines - Web data extraction using appropriate tools such as Scrapy or Playwright - API development using FastAPI or similar - Data cleaning, matching, deduplication and validation - Full-stack dashboard development - Production deployment and documentation **Preferred:** - LLM integrations: Claude, OpenAI or Gemini - LangGraph or similar workflow orchestration - RAG and GraphRAG - Knowledge graphs - MCP servers - n8n - Cloud deployment: AWS, GCP or equivalent - B2B lead generation and business intelligence systems ## Initial Scope — 30-Day MVP We want to begin with Varanasi, Uttar Pradesh. The first phase should deliver: 1. A working PostgreSQL database. 2. A structured database of relevant local businesses. 3. Source-backed company and project records. 4. A basic relationship mapping system. 5. Transparent lead scoring. 6. A functional sales dashboard. 7. Prospect search, filtering and follow-up tracking. 8. CSV/Excel export. 9. A documented data collection and validation pipeline. 10. A live demonstration of the working platform. We expect a phased approach. The first milestone should be a focused pilot before expanding the system. ## Deliverables - Complete source code. - Database schema and data models. - Working dashboard and backend. - Data collection and enrichment pipelines. - AI workflows, if applicable. - Deployment configuration. - Technical documentation. - Setup instructions. - Testing and validation. - Project handover. All project-specific source code, databases, documentation and deliverables must be owned by Vidya Timber. Third-party tools and services should be clearly documented. ## Who We Are Looking For We are looking for someone who: - Has built production-grade data pipelines or business intelligence systems. - Can demonstrate relevant completed projects. - Understands the difference between collecting leads and generating actionable intelligence. - Can explain technical decisions in business terms. - Is capable of working independently. - Is interested in a long-term technical partnership. - Can begin with a paid pilot and scale based on results. We are not looking for someone who only builds basic chatbots, generic CRM systems or AI demos. ## Application Questions Please answer the following questions in your proposal: 1. Describe one production-grade B2B data pipeline or business intelligence platform you have developed. 2. How would you discover construction projects in Varanasi and Uttar Pradesh beyond RERA databases? 3. How would you connect architects, builders, contractors and construction projects in a relational database? 4. Would you recommend GraphRAG for the MVP? Why or why not? 5. How would you estimate the potential demand for doors and interior materials from a construction project? 6. What would you include in a 60-hour pilot? 7. What is your estimated timeline and budget for a 30-day MVP? 8. What would the estimated monthly infrastructure and AI API costs be? 9. Can you demonstrate a working production project? 10. Will you personally develop the system, or will other team members be involved? ## Engagement We prefer a paid initial pilot with clearly defined deliverables and milestones. Successful execution may lead to a long-term engagement involving expansion across Uttar Pradesh and additional AI-powered business intelligence capabilities. Please include your hourly rate, estimated hours, proposed architecture and relevant portfolio links. **Our priority is data quality, actionable business intelligence, reliability and measurable commercial value—not unnecessary technical complexity.**