# What Is Data Engineering? Complete Data Engineer Roadmap 2026 | AWS Project + AI

> What data engineers actually do, the skills to learn — SQL, Python, data modeling, PySpark, AWS, Airflow, Snowflake — how a real AWS pipeline fits together, and how AI is changing the job.

- Source: https://akshaythakare.com/videos/data-engineering-roadmap-2026
- Video: https://www.youtube.com/watch?v=0bpR1V3T5cg
- Technologies: SQL, Python, PySpark, AWS Glue, Amazon S3, Snowflake, Apache Airflow, Data modeling
- Published: 2026-10-04
- Updated: 2026-10-11

What data engineers actually do, the skills to learn — SQL, Python, data modeling, PySpark, AWS, Airflow, Snowflake — how a real AWS pipeline fits together, and how AI is changing the job.

## Chapters

- [0:00](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=0s) Introduction to data engineering
- [1:39](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=99s) SQL fundamentals
- [2:37](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=157s) Python and data modeling
- [5:06](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=306s) Distributed processing with Spark
- [5:22](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=322s) Cloud platforms and services
- [5:45](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=345s) Orchestration and automation
- [7:14](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=434s) Building real-world pipelines
- [10:20](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=620s) AI in data engineering
- [11:13](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=673s) Maintaining data systems
- [12:46](https://www.youtube.com/watch?v=0bpR1V3T5cg&t=766s) Learning roadmap and conclusion

## What this video covers

If you are planning to become a data engineer and don't know where to start, this is the map: what the job really is, the skills that matter, and how they come together in a real pipeline.

## The skills, in learning order

| Skill | What to focus on |
| --- | --- |
| SQL | Joins, CTEs, window functions, query optimisation |
| Python | Fundamentals and automation |
| Data modeling | Star schema, fact and dimension tables |
| Warehousing | Data lakes, warehouses and lakehouses |
| PySpark | Distributed processing for big data |
| AWS | S3, Glue, Redshift, IAM |
| Apache Airflow | Workflow orchestration |
| Snowflake | Modern cloud data warehousing |
| AI in data engineering | AI-assisted development with ChatGPT and Claude |

## The real-world pipeline

```mermaid
flowchart LR
  S[Data sources] --> G[AWS Glue] --> S3[(Amazon S3)] --> SF[(Snowflake)] --> A[Analytics & AI/ML]
  AF[Apache Airflow] -. orchestrates .-> G
  AF -. orchestrates .-> SF
```

The full, documented version of this architecture — with code, failure handling and an honest verification record — is the [flagship case study](/projects/aws-snowflake-pipeline).