Skills to Put on a Resume:
The Complete List by Job Type
The wrong skills list is worse than no skills list. It dilutes your keyword density, signals poor targeting, and tells a recruiter you sent a generic resume. Here is exactly what to include — by role type, with the rules that determine what stays and what goes.
Specific tools and technologies — ATS matches on exact terms
Use the posting's exact vocabulary — "Salesforce" not "CRM tools"
Demonstrate them, don't just list them
Lead with skills the posting explicitly requires
The skills section on most resumes is doing less work than it could. Candidates list either too many skills (everything they have ever touched) or too few (just the obvious), and almost never tailor them to the specific role they are applying for. The result is a skills section that passes ATS by accident rather than by design.
This guide covers the skills that matter by category and by role type — including specific examples, the difference between hard and soft skills, and how to format the section for maximum ATS and recruiter impact.
Hard Skills vs Soft Skills — Why the Distinction Matters
| Hard Skills | Soft Skills | |
|---|---|---|
| What they are | Specific, learnable, measurable — tools, technologies, methodologies, certifications | Interpersonal and character-based — communication, leadership, adaptability |
| ATS matching | Strong — ATS is designed to match specific technical terms | Weak — soft skill terms are generic and rarely used as ATS filters |
| Recruiter value | High — immediately evaluable: can you use Python? Can you run Salesforce? | Low as a list — every candidate claims them; unverifiable on their own |
| How to include | Explicitly in the Skills section with exact tool names | Through specific accomplishment bullets — demonstrate, don't list |
| Examples | Python, Salesforce, Google Analytics, SQL, Figma, AWS, Excel | Communication, leadership, teamwork, problem-solving, adaptability |
The One Rule That Determines Everything
Your skills section should reflect the job posting you are applying to — not your full career history.
Before finalizing your skills section for any application, open the job description. Read the Requirements and Responsibilities sections. Every tool, technology, methodology, and domain term they mention is a potential keyword. Your skills section should lead with the ones you genuinely have that the posting explicitly requests.
Skills: Python, JavaScript, React, Node.js, SQL, PostgreSQL, MongoDB, AWS, Docker, Kubernetes, Kafka, Redis, Git, Jira, Confluence, Slack, Excel, PowerPoint, Communication, Teamwork, Leadership
Problem: 20 items, no prioritization, two soft skills at the end. ATS cannot tell what is most important. Neither can the recruiter.
Languages: Go, Python, TypeScript
Infrastructure: AWS (Lambda, SQS, ECS), Kafka, Kubernetes, Docker
Databases: PostgreSQL, Redis, DynamoDB
Tools: Datadog, GitHub Actions, Terraform
Matches posting vocabulary exactly. Grouped for readability. Relevant to this specific role. Soft skills removed — demonstrated in bullets instead.
Skills to Include by Role Type
Software Engineering
Technical skills are the primary evaluation criterion. Group by category — Languages, Frameworks, Databases, Infrastructure, Tools. Use exact names with correct capitalization: "JavaScript" not "javascript," "PostgreSQL" not "postgres."
| Category | Examples | Notes |
|---|---|---|
| Languages | Python, JavaScript, TypeScript, Go, Java, C++, Rust, Swift, Kotlin, Ruby | List only languages you have used in production or substantive projects |
| Frontend frameworks | React, Vue, Angular, Next.js, Svelte | Include version if significantly different from current (React 18 vs React 15) |
| Backend frameworks | Node.js, Django, FastAPI, Spring Boot, Rails, Express, NestJS | — |
| Databases | PostgreSQL, MySQL, MongoDB, Redis, DynamoDB, Snowflake, BigQuery, Elasticsearch | Distinguish SQL vs NoSQL exposure if relevant |
| Cloud / Infrastructure | AWS, GCP, Azure, Kubernetes, Docker, Terraform, Ansible, CI/CD (GitHub Actions, Jenkins) | Specify cloud provider — "AWS" not "cloud" |
| AI / ML (if applicable) | PyTorch, TensorFlow, scikit-learn, LangChain, Hugging Face, OpenAI API | Include only if genuinely used — not for keyword stuffing |
| Tools | Git, GitHub, Jira, Datadog, Sentry, Figma (for design collab), Postman | — |
Data Analyst / Data Scientist
| Category | Examples |
|---|---|
| Languages | Python (pandas, NumPy, scikit-learn), R, SQL |
| Visualization | Tableau, Power BI, Looker, Matplotlib, Plotly, D3.js |
| Databases / Warehouses | PostgreSQL, BigQuery, Snowflake, Redshift, dbt |
| ML / Statistics | Regression, classification, clustering, A/B testing, hypothesis testing, time series |
| Pipelines / Orchestration | Airflow, dbt, Spark, Kafka, Fivetran |
| Spreadsheets / BI | Excel (advanced — VLOOKUP, pivot tables, Power Query), Google Sheets |
Product Manager
PM skills are a mix of tools, methodologies, and domain knowledge. The methodology terms matter — "Agile," "Scrum," "OKRs," "product-led growth" are ATS keywords in PM job postings.
| Category | Examples |
|---|---|
| Methodology | Agile, Scrum, Kanban, OKRs, product-led growth, jobs-to-be-done, design thinking |
| Analytics | Mixpanel, Amplitude, Google Analytics, Heap, SQL (basic), A/B testing |
| Roadmapping / PM tools | Jira, Linear, Productboard, Notion, Aha!, Confluence |
| Design collaboration | Figma, Miro, Whimsical, FigJam |
| Research | User interviews, usability testing, survey design, Dovetail, UserTesting |
| Domain (if applicable) | B2B SaaS, marketplace, fintech, healthtech, developer tools, enterprise software |
Marketing
Marketing skills vary significantly by specialization. Lead with the channel or function the posting emphasizes — demand gen, content, SEO, paid, brand.
| Specialization | Key Skills |
|---|---|
| Demand Generation | HubSpot, Marketo, Pardot, Salesforce, Google Ads, LinkedIn Ads, MQL/SQL pipeline, ABM |
| Content Marketing | SEO (on-page, technical), WordPress, HubSpot, Ahrefs, Semrush, content strategy, editorial planning |
| Paid Advertising | Google Ads, Meta Ads Manager, LinkedIn Ads, programmatic, attribution modeling, ROAS, CAC |
| Email Marketing | Klaviyo, Mailchimp, Iterable, A/B testing, deliverability, segmentation, lifecycle marketing |
| Analytics | Google Analytics 4, Mixpanel, Looker, Tableau, SQL (basic), attribution, UTM tracking |
| Brand / Creative | Figma, Canva, Adobe Creative Suite (Photoshop, Illustrator, Premiere), brand guidelines |
Finance and Accounting
| Function | Key Skills |
|---|---|
| FP&A | Financial modeling, Excel (advanced), Google Sheets, Anaplan, Adaptive, Tableau, variance analysis, forecasting |
| Accounting | QuickBooks, NetSuite, SAP, Xero, GAAP, IFRS, reconciliation, month-end close, audit |
| Investment / M&A | DCF, LBO modeling, comparable analysis, Bloomberg Terminal, PitchBook, FactSet, capital markets |
| Credentials | CPA, CFA, CIMA, ACCA, Series 7/63/65 — spell out full credential name, not just abbreviation |
Sales
| Category | Examples |
|---|---|
| CRM | Salesforce, HubSpot, Pipedrive, Outreach, Salesloft, Gong, Chorus |
| Methodology | MEDDIC, SPIN, Challenger, solution selling, consultative selling, value-based selling |
| Market segment | SMB, Mid-Market, Enterprise, inbound, outbound, PLG (product-led growth) |
| Metrics | ARR, MRR, ACV, quota attainment, pipeline coverage, win rate, CAC, churn |
HR and People Operations
| Category | Examples |
|---|---|
| HRIS | Workday, BambooHR, ADP, UKG, Greenhouse, Lever, iCIMS |
| Recruiting | LinkedIn Recruiter, Boolean search, candidate sourcing, ATS management, structured interviews |
| Compliance | FMLA, ADA, EEO, FLSA, I-9 verification, labor law (specify jurisdiction) |
| L&D | Instructional design, LMS (Cornerstone, Workday Learning, TalentLMS), Articulate 360 |
| Compensation | Compensation benchmarking, Radford, Mercer, equity plan administration, pay equity analysis |
Operations and Project Management
| Category | Examples |
|---|---|
| Project management | PMP, Agile, Scrum, Kanban, Jira, Asana, Monday.com, MS Project, Smartsheet |
| Process improvement | Lean, Six Sigma (specify belt level), Kaizen, process mapping, BPMN |
| Automation | Zapier, Make (Integromat), Python (scripting), RPA tools (UiPath, Automation Anywhere) |
| Supply chain | ERP (SAP, Oracle, NetSuite), inventory management, logistics, vendor management, procurement |
Design (UX/UI and Graphic)
| Category | Examples |
|---|---|
| Design tools | Figma, Sketch, Adobe XD, InVision, Zeplin, Framer |
| Graphic / Motion | Adobe Photoshop, Illustrator, InDesign, After Effects, Premiere Pro |
| Research methods | User interviews, usability testing, card sorting, journey mapping, A/B testing, heuristic evaluation |
| Prototyping | Figma prototyping, ProtoPie, Marvel, interactive wireframing |
| Design systems | Component libraries, design tokens, accessibility (WCAG 2.1), responsive design |
Healthcare (Clinical and Administrative)
| Category | Examples |
|---|---|
| EHR / EMR Systems | Epic, Cerner, Meditech, Allscripts, eClinicalWorks, Athenahealth |
| Clinical | Patient assessment, triage, medication administration, ICD-10 coding, CPT coding |
| Certifications | BLS, ACLS, PALS, CNA, CMA, RN license, NPI number — always spell out in full |
| Compliance | HIPAA, Joint Commission standards, infection control protocols, OSHA |
Skills That Work Across Most Roles
Some hard skills appear in job postings across multiple industries and functions. These are worth including if you genuinely have them and they are relevant to the target role:
| Skill | Relevant to | Notes |
|---|---|---|
| SQL | Engineering, data, finance, marketing, operations | Specify level: basic querying vs complex joins vs stored procedures |
| Excel / Google Sheets | Almost every professional role | Specify level: "Excel (advanced: pivot tables, VLOOKUPs, Power Query)" |
| Python (scripting) | Engineering, data, finance, operations, marketing | Specify context: data analysis, automation, API integration |
| Salesforce | Sales, marketing, customer success, operations | Specify if certified: Salesforce Administrator, Sales Cloud, Service Cloud |
| Tableau / Power BI | Data, finance, marketing, operations, strategy | Specify which one — they are different tools with different job market demand |
| Project management tools | Nearly all roles | Name the specific tool: Jira, Asana, Monday.com — not "project management software" |
| G Suite / Microsoft 365 | All office-based roles | Worth including for roles where administrative capability matters |
What Not to Include in Your Skills Section
Generic soft skills as standalone items
"Communication," "leadership," "teamwork," "problem-solving," "attention to detail" — listed without demonstration. These words appear on almost every resume. ATS does not prioritize them for most roles, and recruiters have been conditioned to ignore them. If these qualities matter to you, show them in bullets. A bullet that reads "Led cross-functional alignment across engineering, legal, and customer success to ship a GDPR compliance feature in 6 weeks" demonstrates communication and leadership without claiming them explicitly.
Outdated technology that signals age
Microsoft FrontPage. Adobe Flash. Windows XP administration. WordPerfect. These signal that your skill set has not been updated recently. Remove anything that is no longer in active professional use.
Skills so basic they go without saying
"Internet browsing," "Microsoft Word," "email" for professional roles. "Able to lift 30 pounds" for office jobs. These waste space and lower the signal-to-noise ratio of the section.
Skills you cannot actually demonstrate
Listing a tool you experimented with once three years ago and have not touched since is a liability if it comes up in an interview. "Walk me through your experience with Salesforce" when your answer is "I set it up briefly for a side project" will damage your credibility on everything else you listed. Only include skills you can speak to substantively.
The same skills listed in multiple sections
If Python appears in your skills section, in your summary, and in three bullets — it does not need to appear in four different places. Once in the skills section and once in a relevant bullet is sufficient. Repetition beyond that suggests you are padding rather than informing.
How to Format the Skills Section
Use categories, not a flat list
A flat list of 20 skills with no structure is harder to read and harder for ATS to process than a grouped list. Group by category — Languages, Tools, Frameworks, Certifications, Methodologies. The number of categories depends on the role; three to five is typical.
Python, SQL, Tableau, Salesforce, Excel, HubSpot, Jira, PowerPoint, Google Analytics, A/B testing, communication, leadership, Excel, project management, Slack, Notion, Asana
Analytics: Python (pandas, NumPy), SQL, Google Analytics 4, Tableau
Marketing Tools: HubSpot, Salesforce, Klaviyo, Semrush
Project Management: Jira, Asana, Notion
Certifications: Google Analytics Certified, HubSpot Content Marketing
Lead with the posting's requirements
Within each category, put the skills the posting explicitly requires first. If the posting says "proficiency in Tableau required" and "familiarity with Power BI preferred" — Tableau leads your visualization category. ATS scoring weights terms that appear earlier in the document more heavily in some platforms.
Use exact names and correct capitalization
ATS platforms vary in case-sensitivity, but the safest approach is to spell tools exactly as they appear in the job posting: "JavaScript" not "Javascript," "GitHub" not "Github," "Google Analytics" not "google analytics." When in doubt, check the tool's own website for the official spelling.
Do not use skill bars or rating systems
Visual skill proficiency bars ("Python ????0") communicate nothing to ATS — they are image-based and not parsed as text. They also create an uncomfortable problem: no one agrees what "4 out of 5 stars" means for Python proficiency. Remove them and replace with the tool name in plain text with context if needed: "Python (pandas, NumPy, 5 years production use)" tells a recruiter far more than a filled circle.
For the full skills section guide including ATS rules: Resume Skills: How to Write the Skills Section. For how to list computer skills specifically: Computer Skills for Resume. For how deep your work history should go to match your skills section: How Far Back Should a Resume Go? For the opening statement that introduces your skills to a recruiter: Objective for Resume vs Professional Summary.
How Skills Sections Change at Different Career Stages
| Stage | What to emphasize | Length | Notes |
|---|---|---|---|
| Student / Entry level | Tools from coursework, personal projects, certifications, any relevant software | 1–2 categories, 5–10 items | Certifications matter more here — they signal intentional learning |
| Early career (2–5 years) | Tools used in professional context, methodologies adopted, growing specialization | 2–3 categories, 8–15 items | Remove skills from school projects not used professionally |
| Mid career (5–10 years) | Specialized proficiency, advanced tool knowledge, leadership methodologies | 3–5 categories, 12–20 items | Start removing skills you have moved beyond; depth over breadth |
| Senior / Executive | Strategic tools and methodologies; remove basic operational skills | 3–4 categories, 10–15 focused items | A senior leader listing "Microsoft Word" looks like they haven't updated their resume in a decade |
Emerging Skills Worth Adding Now
These skills have seen rapid growth in job postings and carry a meaningful wage premium or differentiation value even for non-technical candidates:
| Skill | Relevant roles | How to list it | Why it matters |
|---|---|---|---|
| AI tool fluency (Claude, ChatGPT, Perplexity) | Marketing, operations, HR, finance, PM, writing | Name specific tools + specific use case: "Claude (stakeholder communication drafting)" | 56% wage premium for AI-skilled workers in the same role — PwC |
| Prompt engineering | Any role using AI tools, content, operations, engineering | "Prompt engineering (workflow automation, content generation)" | 135% YoY growth in job postings mentioning prompt engineering |
| AI coding tools (GitHub Copilot, Cursor) | Software engineering | "GitHub Copilot" as a tool in your tools category | Signals you are working with the current standard, not against it |
| LLM integration (LangChain, OpenAI API) | Engineering, data, product | List as a tool in appropriate category with context | Rapidly becoming a standard expectation in tech hiring |
| Data visualization (Tableau, Power BI, Looker) | Finance, marketing, operations, strategy, PM | Name the specific platform | Among the most commonly searched skills in non-engineering roles |
| No-code / low-code tools (Zapier, Make, Airtable) | Operations, marketing, small team environments | "Zapier, Make (workflow automation)" with specific processes automated | High value in lean teams; signals problem-solving initiative |
The rule for emerging skills is the same as for established ones: only list them if you have genuinely used them and can speak to specific use cases in an interview. "AI skills" as a generic claim without named tools and specific applications adds nothing. For the full guide on adding AI skills to your resume: AI Skills for Resume: What to Add and How to List Them.
Skills Section vs Experience Bullets — Which Carries More Weight?
Both matter, but for different reasons and at different stages of the screening process.
The skills section is the primary ATS keyword-matching zone. It gets scanned in the first pass — the automated layer that filters before any human sees your resume. A well-constructed skills section with the right terminology ensures you pass this filter.
Experience bullets are what a human reads after you pass ATS. They provide context, proof, and specificity. A skill listed in your skills section but never mentioned in context carries less credibility than one that appears in both — "Python" in your skills section plus "Built a Python automation script reducing manual data processing from 6h to 15 minutes" in a bullet is far stronger than either alone.
The highest-value resume strategy is to have your key skills appear in three places: the skills section (keyword matching), the summary (context and positioning), and at least one bullet (evidence and proof). This is called the three-layer approach and it significantly improves both ATS scoring and recruiter conversion.