Home / Roadmaps / Data Engineering
Data Engineering
Build the pipelines and warehouses everyone else's data depends on.
Data engineering is the plumbing of the data world: ingesting, transforming, and serving data reliably at scale. It is one of the best-paid and most durable data roles, and it rewards strong software engineering habits.
The route
Programming & SQL depth 6–10 weeks
Production-grade Python and advanced SQL are non-negotiable foundations.
- Python
- Advanced SQL
- Data modeling
- Git & testing
Warehouses & transformation 6–10 weeks
Learn a cloud warehouse and the modern transformation layer that sits on top of it.
- BigQuery / Snowflake
- dbt or SQL transforms
- Dimensional modeling
- Partitioning & cost
Orchestration & pipelines 8–12 weeks
Move data on a schedule, reliably, with monitoring and retries.
- Airflow / Dagster
- Batch & streaming
- APIs & ingestion
- Idempotency & watermarks
Cloud, infra & a capstone 8–12 weeks
Tie it together on a cloud platform with a real, scheduled pipeline you can demo.
- GCP / AWS basics
- Docker
- CI/CD for data
- End-to-end capstone
Who it's for
- Analysts who like building systems more than charts
- Backend developers moving into data
- People who enjoy reliability and automation
Career outcomes
- Data Engineer
- Analytics Engineer
- ETL/ELT Developer
Prefer guided learning?
If self-paced study keeps stalling, a mentored cohort can get you to job-ready faster. DTI runs structured programs in Albania across software, data, and security.
Explore DTI →