Python for Data Engineers
2-3 weeksSkills You'll Build
Python fundamentals for dataPandas and data manipulationWorking with APIsFile formats (JSON, Parquet, Arrow)Virtual environments and package management
Data Warehouse Engineer → AI Data Architect
Data Warehouse Engineer to AI Data Architect
Transition from data warehouse engineering to AI-focused data architecture. Your expertise in data modeling, ETL pipelines, and SQL optimization gives you a strong foundation for AI data infrastructure. Learn to design vector databases, manage embeddings at scale, and build the data layer that powers production AI systems.
4-6 months
Prerequisites
- Data modeling and schema design
- SQL optimization and query performance
- ETL/ELT pipeline development
- Star schema and dimensional modeling
- Experience with data warehouses (Snowflake, BigQuery, Redshift)
Your Learning Path
Vector Databases and Embeddings
3-4 weeksSkills You'll Build
Understanding embeddingsVector database architectureIndexing strategies (HNSW, IVF)Hybrid search implementationPerformance optimization
AI Data Pipeline Architecture
4-5 weeksSkills You'll Build
Embedding generation pipelinesChunking strategiesData versioning for AIReal-time vs batch processingCost optimization
RAG System Data Layer
4-5 weeksSkills You'll Build
RAG architecture patternsDocument ingestion pipelinesMetadata managementQuery optimizationCaching strategies
Production Deployment and Portfolio
3-4 weeksSkills You'll Build
Infrastructure as codeMonitoring AI data pipelinesPortfolio project showcasing data architectureInterview preparationSalary negotiation