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Résumé keywords · Oct 2026

Data Engineer résumé keywords

We read 62 open Data Engineer job posts from 32 companies. The skills and tools they ask for most: SQL (85%), Python (79%), Data Engineering (77%).

  • Posts ask for skills more than specific tools — 8 of the top 10 keywords are skills or domains.
  • Employers also stress collaboration (74% of posts) and stakeholder management (61%) — show them through results, not adjectives.
  • Anthropic stands out: its Data Engineer posts mention Logistics and ETL far more than the average.
  • O*NET flags Amazon Web Services AWS, Apache Kafka, Apache Spark as in demand for this occupation.

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The top 30 Data Engineer keywords

Skills, tools and domains — share of job posts that mention each at least once. Soft skills are listed under “By type”.

Must-havein half or more of posts

  1. SQL85%
  2. Python79%
  3. Data Engineering77%
  4. Analytics50%

Commonin 25–49% of posts

  1. dbt48%
  2. Data Modeling42%
  3. Airflow42%
  4. Machine Learning42%
  5. ETL37%
  6. Observability37%
  7. Snowflake34%
  8. Apache Spark34%
  9. Databricks26%

Worth havingin 10–24% of posts

  1. A/B Testing24%
  2. Git23%
  3. BigQuery23%
  4. AWS23%
  5. LLM21%
  6. GCP21%
  7. Apache Kafka19%
  8. CI/CD18%
  9. Looker16%
  10. Backend16%
  11. Tableau15%
  12. Java15%
  13. Scala15%
  14. Accessibility15%
  15. Salesforce13%
  16. Distributed Systems13%
  17. Data Analysis13%

By type

Skills

  • SQL 85%
  • Python 79%
  • Data Engineering 77%
  • Data Modeling 42%
  • Machine Learning 42%
  • ETL 37%
  • Observability 37%
  • A/B Testing 24%
  • LLM 21%
  • CI/CD 18%
  • Backend 16%
  • Java 15%
  • Scala 15%
  • Accessibility 15%

Tools & software

  • dbt 48%
  • Airflow 42%
  • Snowflake 34%
  • Apache Spark 34%
  • Databricks 26%
  • Git 23%
  • BigQuery 23%
  • AWS 23%
  • GCP 21%
  • Apache Kafka 19%
  • Looker 16%
  • Tableau 15%
  • Salesforce 13%
  • Azure 11%

Soft skills

  • Collaboration 74%
  • Stakeholder Management 61%
  • Communication 50%
  • Ownership 31%
  • Leadership 21%
  • Mentoring 19%

Domain knowledge

  • Analytics 50%
  • Logistics 11%

What hiring companies emphasise

Companies with the most open Data Engineer roles in our sample, and the terms they mention more than the average post.

  • Anthropic

    5 open roles

    Logistics · ETL · dbt

  • Coinbase

    5 open roles

    Generative AI · Statistics · LLM

  • Faire

    4 open roles

    Accessibility · Docker · Machine Learning

  • Roblox

    4 open roles

    A/B Testing · Apache Spark · Machine Learning

  • Block

    3 open roles

    Fintech · Git · Snowflake

  • Samsara

    3 open roles

    Cloud Computing · Backend · AWS

  • SpaceX

    3 open roles

    C++ · C# · Forecasting

  • Affirm

    2 open roles

    REST · Git · Snowflake

How to put these keywords in your résumé

A keyword counts most inside a bullet that proves it — an action, the tool, and a result. Real bullets from our example résumés:

The occupation: Database Architects

Design strategies for enterprise databases, data warehouse systems, and multidimensional networks. Set standards for database operations, programming, query processes, and security. Model, design, and construct large relational databases or data warehouses. Create and optimize data models for warehouse infrastructure and workflow. Integrate new systems with existing warehouse structure and refine system performance and functionality.

Most important skills (O*NET, 1–5)

  • Reading Comprehension3.9
  • Critical Thinking3.9
  • Active Listening3.5
  • Speaking3.5
  • Active Learning3.3
  • Writing3.1
  • Monitoring3.1
  • Mathematics3.0

In-demand technology

Software O*NET flags for this occupation as in demand by employers or “hot” across job postings.

  • Amazon Web Services AWS
  • Apache Kafka
  • Apache Spark
  • Microsoft Azure
  • Microsoft Excel
  • Microsoft Office
  • Microsoft Power BI
  • Microsoft PowerPoint
  • Oracle Java
  • Python
  • Snowflake
  • Structured query language SQL
  • Tableau
  • Adobe Acrobat
  • AJAX
  • Amazon DynamoDB

Data Engineer résumé keyword questions

What keywords should a Data Engineer résumé include?
The skills and tools Data Engineer job posts mention most are SQL (85%), Python (79%), Data Engineering (77%), Analytics (50%), dbt (48%), Data Modeling (42%), Airflow (42%), Machine Learning (42%), ETL (37%), Observability (37%) — based on 62 open posts at 32 companies (Oct 2026). Include the ones you genuinely have, in your skills section and in the bullets that prove them.
Which tools do Data Engineer job posts ask for?
Most often: dbt (48% of posts), Airflow (42% of posts), Snowflake (34% of posts), Apache Spark (34% of posts), Databricks (26% of posts), Git (23% of posts).
Which soft skills matter for a Data Engineer?
Job posts mention collaboration (74%), stakeholder management (61%), communication (50%), ownership (31%), leadership (21%). Show them through results in your bullets rather than listing them.
Should I add every keyword to my résumé?
No. Add a keyword only if it's true for you — then show it in a bullet with a result. Applicant tracking systems match keywords, but a recruiter reads the résumé next, and unsupported buzzwords cost interviews.

Keep going

Keyword shares: Public job boards (Greenhouse, Lever) of 79 companies, Oct 2026. We count how many open posts for this role mention each term at least once; the same opening listed in several cities counts once. No post text is stored.

This page includes information from the O*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. GotOffered has modified all or some of this information. USDOL/ETA has not approved, endorsed, or tested these modifications.