Choose Your Learning Path¶
Select the path that matches your role and goals. Each path is designed to take you from beginner to proficient in about 90 minutes.
Quick Start Prerequisite¶
Before starting any path, complete the 10-Minute Quick Start to learn the basics of Seeknal.
Learning Paths¶
Data Engineer Path¶
Who it's for: Data engineers building ETL/ELT pipelines, data infrastructure, and production data systems.
What you'll learn: - Build complete ELT pipelines with YAML and Python - Implement incremental processing for efficiency - Manage production environments safely
Time commitment: 3 chapters × 20-30 minutes
Analytics Engineer Path¶
Who it's for: Analytics engineers defining metrics, building semantic layers, and enabling self-serve analytics.
What you'll learn: - Define semantic models for consistent metrics - Create business metrics (KPIs, ratios, cumulative) - Deploy metrics for BI tool consumption
Time commitment: 3 chapters × 20-30 minutes
Start Analytics Engineer Path →
ML Engineer Path¶
Who it's for: ML engineers building feature stores, computing features for ML models, and managing training-to-serving parity.
What you'll learn: - Build feature groups with point-in-time joins - Create second-order aggregations for ML features - Train and serve ML models inside the pipeline - Consolidate multiple feature groups into unified entity views
Time commitment: 4 chapters (~115 minutes)
Not Sure Where to Start?¶
Choose Data Engineer Path if you want to understand Seeknal's core data transformation capabilities first.
Choose Analytics Engineer Path if you're focused on metrics, BI, and business intelligence.
Choose ML Engineer Path if you're building ML systems and need feature management.
Advanced Guide¶
After completing a learning path, level up with the Advanced Guide covering:
- File Sources — Load CSV, Parquet, and JSONL data
- Data Rules — Validate data quality with automated checks
- Lineage & Inspection — Visualize data flow and debug outputs
- Named ref() References — Self-documenting, reorder-safe SQL references
- Common Configuration — Shared column mappings, rules, and SQL snippets
- Python Pipelines — Build nodes with Python decorators
- Database & External Sources — Connect to PostgreSQL, StarRocks, and Iceberg
Time commitment: 9 chapters (~180 minutes)
Path Completion¶
Each path ends with a completion page summarizing what you've learned and suggesting next steps. You can complete multiple paths to become a Seeknal expert.
Ready to begin? Make sure you've completed the Quick Start first!