Data Engineer Resume Keywords

Skills, tools and practices

How many of the 173 postings mention each term at least once. The last column shows the share among the 48 India-located postings.

Reading the table

• In the 48 India-located postings, ETL appeared more often (60% against 43% overall) and dbt less often (15% against 32%).
• Tool names vary by employer. If the ad names Databricks and you used Spark on EMR, say Spark and the platform you used; do not swap one for the other.

Working-style words

Words such as "communication" appear in most ads for most roles. They show what employers say they value; on a resume they only count when a bullet shows them in action.

Example bullets that use these keywords

• Built [n] Airflow DAGs that load [sources] into Snowflake, with data-quality checks on [fields or rules].
• Rewrote a Spark job that [does what]; run time fell from [x] to [y] and compute cost from [a] to [b] a month.
• Modelled [domain] data in dbt (staging and marts) used by [n] dashboards across [teams].
• Added data-quality tests and alerting for [n] tables; [n] issues were caught before reaching dashboards.
• Migrated [n] ETL jobs from [old tool] to [new tool], with CI/CD for SQL and Python.

Brackets mark numbers and details only you know. Fill them in from your own records, or leave the number out. Do not estimate.

How to use this list

1. Start from the job ad you are answering. This table shows what is common across many ads; the ad in front of you is what gets read.
2. Use a term only where it describes work you did, inside a bullet that shows how you used it. A list of skills on its own proves little.
3. Match the employer’s wording, for example "FP&A" or "financial planning and analysis", whichever the ad uses.
4. To compare your resume with one job description, use the job description match (free account, 2 credits). To see what a parser reads from your PDF first, run the free check.

Method

• On 12 October 2026 we collected 19,607 job postings from sources that publish them without a login (table below). After removing duplicates, 16,649 remained, of which 1,730 were India-located.
• Which postings count as data engineer roles: titles containing "data engineer", "analytics engineer", "big data engineer" or "data platform engineer" (manager and director titles excluded).
• An ad with the same employer, the same title and the same opening text is counted once, even when it is posted for several cities.
• At most 6 postings per employer per role, so one large employer cannot dominate. When an employer had more, India-located postings were kept first.
• On employer careers sites hosted on Workday we searched for the role name and read up to 8 matching postings per site and search, India-located first, so those postings are a targeted sample rather than everything the site lists.
• Sentences about pay, benefits, equal-opportunity law, privacy and the application process are removed before counting.
• A term counts once per posting if any of its listed spellings appears in the title or the remaining description (case-insensitive, whole words). The share is postings mentioning the term divided by N.
• 401 terms: the skills list used by Resumity's job search tool (minus spellings that are ordinary English words, such as "go", "rest" and "flow"), plus business, finance and HR terms added for this study. Terms outside the list are not counted.
• A term is not counted in postings from an employer whose name contains it (for example "MongoDB" in a MongoDB job ad).
• Terms are grouped into the role’s own skills, tools and practices, working-style words, and terms from other fields (for example "cloud" in a finance ad, usually the employer describing itself). The third group is left out of the tables.
• A posting counts as India-located if its location field names India or an Indian city.

Limits

• Most sources are remote-first job boards and the careers pages of US, European and Indian technology companies and banks, so the sample leans towards those employers and towards remote roles.
• Large Indian job boards such as Naukri and foundit, and LinkedIn, are not included. We used only sources that publish postings as open data without a login.
• The sample for this role is 173 postings from 87 employers, 48 of them India-located.
• A count shows how often a term appears in ads. It does not show how much a recruiter weighs it, or whether any software filters on it.
• This is one day’s snapshot. Ads change every week.
• Terms outside our list are not counted, so a skill missing from the table may still be common.

Related pages

Keyword counts for other roles