AI-Powered Enterprise Data Platform Development

**Title:** Build Enterprise AI Data Platform (CloudObjectIQ) using DuckDB, AI, and Multi-Source Data Connectors We are building **CloudObjectIQ**, an enterprise AI-powered data platform that combines serverless analytics, metadata management, AI-assisted SQL, and document intelligence. ### Project Overview We are looking for an experienced architect/full-stack engineer to build a scalable platform that allows users to connect to multiple enterprise data sources, query data using DuckDB, manage metadata, and interact with data using natural language. ### Phase 1 Requirements #### Data Connectors * Oracle * SQL Server * PostgreSQL * MySQL * SAP * REST APIs * CSV * Excel * Parquet * Iceberg * Delta Lake * Amazon S3 * Azure Data Lake Storage (ADLS) * MinIO #### Metadata Catalog * Connection management * Database, schema, table, and column discovery * Primary and foreign keys * Data lineage * Schema evolution * Query history * Data profiling * Business glossary * Tags and classifications #### Query Engine * DuckDB as the execution engine * Direct querying of Parquet, CSV, Iceberg, and Delta Lake * Cross-source joins * Query optimization * Query history and execution statistics #### AI Features * Natural language to SQL * SQL explanation and optimization * Documentation and PDF search (RAG) * AI-powered data discovery * AI assistant using GPT APIs * Vector search using Milvus #### Security * Role-based access control (RBAC) * Row-level security * Column-level security * OAuth2 / Azure AD / LDAP integration * Secret management #### Administration * Connection manager * Job scheduler * Incremental and CDC ingestion * Monitoring and audit logs * Performance dashboard * Cost and usage analytics ### Preferred Technology Stack * Java (Spring Boot) * React * DuckDB * PostgreSQL * Milvus * MinIO * Kubernetes * Docker * Redis * Apache Airbyte or custom ingestion framework ### Deliverables * Production-ready source code * Well-documented architecture * API documentation * Docker deployment * Kubernetes deployment manifests * Unit and integration tests ### Required Experience * DuckDB * Data engineering * Enterprise metadata management * AI/RAG systems * Vector databases (Milvus or similar) * PostgreSQL * Spring Boot * React * Cloud object storage (S3, ADLS, MinIO) Please share: 1. Similar enterprise data platforms or analytics products you have built. 2. Relevant architecture examples. 3. Your proposed implementation plan. 4. Estimated timeline and milestones.

Project ID: 40547463