Skills you need to be a data engineer
9 skills a hiring manager would actually test for, each with the level this role expects and what it is used for. Not a syllabus — the shape of the job.
Build my path to this roleUpskili checks what you can already do, then sequences only what is missing. No account needed.
What the role requires
Ordered by how much the job depends on it. The bar is the proficiency expected of a competent data engineer — not mastery, and not a passing acquaintance.
-
SQL
Essential
Writes and optimizes complex queries for data pipelines and analytics.
Deep -
Python
Essential
Builds data pipelines, transformations, and automation scripts.
Strong -
Apache Spark
Essential
Processes large-scale datasets in distributed environments.
Strong -
Data modeling
Important
Designs star schemas and normalized models for analytics.
Strong -
Airflow
Important
Orchestrates and schedules complex data workflows.
Strong -
Docker
Important
Packages and ships every service the team runs.
Strong -
dbt
Useful
Manages data transformations with version control and testing.
Strong -
Kafka
Useful
Ingests real-time streaming data into the platform.
Working -
AWS/GCP
Useful
Uses cloud storage and compute services for data workloads.
Working
An order worth learning it in
A list of ten skills is the same unhelpful answer a catalogue gives, just sorted. This is where to actually start.
Start here
Essential to the role, and reachable from a standing start. Everything below rests on these.
- Apache Spark
- Airflow
- Docker
Then this
The rest of what the role is assessed on. Harder, and it builds on the foundation above.
- SQL
- Python
- Data modeling
What sets you apart
Not what gets you hired, but what separates doing the job from being trusted with it.
- dbt
- Kafka
- AWS/GCP
You almost certainly have some of this already.
That is the point of starting from the role rather than a course. Upskili checks what you can do, then builds a path across only the gap.
See my path to data engineer