📚 Professional Resources
A curated collection of resources I frequently reference to stay current across data engineering, cloud security, AI, and compliance domains.
☁️ Cloud Engineering & Architecture
- AWS Well-Architected Framework — Best practices for cloud reliability, security, and cost optimization.
- Databricks Documentation — Unified data and AI platform guides.
- AWS Glue Developer Guide — ETL, schema management, and orchestration reference.
- Delta Lake Docs — Building reliable and auditable data lakes.
🤖 AI, ML & Generative AI
- AWS Bedrock Documentation — Foundation model and GenAI workflow development.
- LangChain Docs — Framework for LLM application development.
- OpenAI API Reference — Language model APIs and integrations.
- AWS AI Security Best Practices — Guidance for securing GenAI and LLM-based architectures.
- Pinecone Vector DB — Managing embeddings for semantic search and retrieval.
🔐 Security, Compliance & Governance
- CompTIA PenTest+ Certification — Practical penetration testing and vulnerability assessment framework for enterprise systems.
- OWASP Top 10 — Standard awareness document for application security risks.
- EU Cyber Resilience Act (CRA) — EU regulation ensuring hardware/software cybersecurity.
- EU Radio Equipment Directive (RED) — Compliance standards for wireless and IoT devices.
- NIST 800-53 — Security and privacy controls for federal systems.
- CycloneDX SBOM Standard — Specification for generating and analyzing software BOMs.
🧰 Coding, Data & Development
- PySpark API Docs — PySpark classes and functions.
- Pandas Documentation — Data analysis and manipulation library.
- SQL Style Guide — Best practices for writing clean SQL.
- Databricks SQL Reference — Query syntax and examples for Delta Lake.
- GitHub Actions — Automating CI/CD pipelines.
🌱 Continuous Learning & Community
- AWS Skill Builder — Free AWS training and labs.
- Coursera — Generative AI with LLMs — Deep dive into building and deploying GenAI solutions.
- LinkedIn Learning: Cloud Security — Industry-recognized cloud and security courses.
- Kaggle — Datasets and community challenges for ML and data analysis.
These curated resources shape my approach to building AI-driven, compliant, and secure cloud data systems — uniting disciplines from data engineering, cloud architecture, and cybersecurity.