Data Engineer resume skills and keywords
In 1,066 Data Engineer job postings from 674 employers analysed on October 23, 2026, the most requested skills are Python (83 %), SQL (79 %), Data Engineering (72 %), Data pipelines (67 %) and AWS (53 %). Of the top 40 skills, 34 are hard skills, tools or certifications and 6 are soft skills.
Download the full list as a CSV or check your own resume against a posting with the free keyword scanner.
Top 40 skills in Data Engineer job postings
| Skill | Share of postings | Type |
|---|---|---|
| Python | 83 % | Tool |
| SQL | 79 % | Tool |
| Data Engineering | 72 % | Hard skill |
| Data pipelines | 67 % | Hard skill |
| AWS | 53 % | Tool |
| Apache Spark | 48 % | Tool |
| Communication | 47 % | Soft skill |
| ETL | 46 % | Hard skill |
| Airflow | 43 % | Tool |
| CI/CD | 40 % | Tool |
| Dbt | 38 % | Hard skill |
| Snowflake | 36 % | Tool |
| Data modeling | 34 % | Hard skill |
| Databricks | 34 % | Tool |
| GCP | 32 % | Tool |
| Collaboration | 32 % | Soft skill |
| Azure | 30 % | Tool |
| APIs | 30 % | Hard skill |
| Mentoring | 28 % | Soft skill |
| Apache Kafka | 27 % | Tool |
| Problem Solving | 25 % | Soft skill |
| Data Processing | 25 % | Hard skill |
| Git | 23 % | Tool |
| Leadership | 23 % | Soft skill |
| Terraform | 23 % | Tool |
| Data Science | 22 % | Hard skill |
| Data Governance | 22 % | Hard skill |
| Lineage | 21 % | Hard skill |
| Infrastructure as code | 20 % | Hard skill |
| BigQuery | 20 % | Tool |
| Code review | 20 % | Hard skill |
| Machine learning | 19 % | Hard skill |
| Kubernetes | 17 % | Tool |
| Decision making | 15 % | Soft skill |
| Redshift | 15 % | Tool |
| LLMs | 15 % | Tool |
| PostgreSQL | 15 % | Tool |
| Docker | 14 % | Tool |
| Java | 14 % | Tool |
| Data Warehousing | 14 % | Hard skill |
Hard skills vs soft skills vs tools and certifications
Hard skills (14)
- Data Engineering 72 %
- Data pipelines 67 %
- ETL 46 %
- Dbt 38 %
- Data modeling 34 %
- APIs 30 %
- Data Processing 25 %
- Data Science 22 %
- Data Governance 22 %
- Lineage 21 %
- Infrastructure as code 20 %
- Code review 20 %
- Machine learning 19 %
- Data Warehousing 14 %
Soft skills (6)
- Communication 47 %
- Collaboration 32 %
- Mentoring 28 %
- Problem Solving 25 %
- Leadership 23 %
- Decision making 15 %
Tools and software (20)
- Python 83 %
- SQL 79 %
- AWS 53 %
- Apache Spark 48 %
- Airflow 43 %
- CI/CD 40 %
- Snowflake 36 %
- Databricks 34 %
- GCP 32 %
- Azure 30 %
- Apache Kafka 27 %
- Git 23 %
- Terraform 23 %
- BigQuery 20 %
- Kubernetes 17 %
- Redshift 15 %
- LLMs 15 %
- PostgreSQL 15 %
- Docker 14 %
- Java 14 %
Keyword phrases recruiters use
Multi-word phrases that recur across these data engineer postings, with the share of postings that use each one.
How to use this on your resume
Treat the table as a checklist, not a script. Put the skills you genuinely have in your skills section, using the same wording as the posting, and back the top ones with a bullet that shows the result.
Each job posting differs from the average, so compare your resume with the actual ad: paste it into the resume keyword scanner to see which terms you already have and which are missing. The ATS keywords guide explains where to place them so applicant tracking systems read them.
Skip any skill you cannot talk about in an interview; a keyword that falls apart under one question costs more than it gains. For a full layout with these skills in context, see the Data Engineer resume example. Then prepare for the Data Engineer interview questions that test them.
Build a data engineer resume with these skills
Start in the editor, tailor your bullets to the job you want and download an ATS-friendly resume.