datastacktv/data-engineer-roadmap resource
Roadmap to becoming a data engineer in 2021 observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2191
- days_rel: n/a
- days_push: 1681
- n_releases_24m: 0
Adoption not part of the score
12749 stars · 1337 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
A visual roadmap and study guide outlining the tools, skills, and landscape of modern data engineering as of 2021. It is a curated reference document (images plus text versions) rather than runnable software.
Use cases
- become a data engineer
- learn data engineering skills
- plan a data engineering career path
- find which data tools to study
- understand the modern data stack landscape
When to choose
- you want a structured overview of data engineering skills and tools
- you are a beginner planning what to learn
- you want a shareable visual curriculum for data engineering
When to avoid
- you need runnable code or a software tool
- you need up-to-date 2024+ tooling guidance since the roadmap targets 2021
- you want interactive lessons rather than a static reference
Facets
learning-resource · maturity maintenance
documentation developer-tools tutorials cloud-computing big-data cross-platform roadmap study-guide career data-engineer infographic data-engineering
1 source
- readme: https://github.com/datastacktv/data-engineer-roadmap · fetched 2026-08-28 · c8a0af20d7c7
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| datastacktv/data-engineer-roadmap | main | 23 |
For agents
markdown · JSON · MCP: product_card(name="datastacktv/data-engineer-roadmap")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem