Shell, Programming Languages, DataFrames, and Database Queries
- Shell — File processing, scripting, and system operations from the command line
- Programming Languages — Python and C# paired notebooks from language foundations to GCP integration
- DataFrames — Pandas and Polars side-by-side: loading, transforming, testing
- Database Queries — SQL Server, BigQuery, and Firestore executable query reference
- SQL Server — Administration, query optimization, pipeline patterns, and the medallion implementation
- PostgreSQL — Cluster operations, storage internals, planner behavior, and pipeline patterns on the migrated
stoxx lab
- GCP — Compute, BigQuery, Firestore, GCS, security, identity, and cost management
- Terraform — Infrastructure as code: HCL fundamentals, GCP resources, patterns, and block library
- Docker — Container lifecycle, image management, and Docker Compose orchestration
dbt, Orchestration, and Data Architecture
- dbt — SQL transformation layer: modeling, testing, macros, adapters, and CI/CD
- Orchestration — Airflow DAG patterns, scheduling, and data ingestion frameworks
- Data Architecture — System blueprints, pipeline patterns, data modeling, reliability, and decision frameworks
Git, GitHub Actions, and CI/CD
- Git — Daily workflow, branching, collaboration, and recovery
- GitHub Actions — Workflow fundamentals, CI/CD patterns, and data engineering automation
Observability, Monitoring, and Alerting
- Observability — Datadog platform, GCP-native monitoring, and observability strategy
DataOps, Practice, and Leadership
- DataOps — DataOps principles, team organization, self-service platforms, and engineering leadership
AI, Prompt Engineering, and LLM Pipelines
- AI & Prompts — Prompt engineering, LLM pipeline integration, output validation, and financial guardrails
Financial Markets, Scoring, and Regulation
- Financial Domain — Sector encyclopedias, market analysis, scoring methodology, regulatory compliance, and the ISS-STOXX glossary
