Updated on August 24, 2026
150+ Technical Skills to Put on Your Resume in 2026
Technical skills for your resume across 17 fields, from Epic and CAD to GA4 and Python, with a copyable skills-block format and honest skill tiers.

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Choosing the right technical skills for your resume is harder than it looks. Many candidates either list every tool they have ever used or include vague skills that do not match what employers are actually searching for.
The wrong skills can make your resume harder to scan, weaken your credibility, and leave hiring managers unsure whether you have the experience the role requires. Even strong technical abilities can get overlooked if they are buried, poorly organized, or described without the right context.
This guide helps you identify the technical skills that matter most for your field, organize them in an ATS-friendly way, and present your proficiency honestly. You will find 150+ technical skills across 17 industries, plus practical examples for building a resume skills section that gets noticed.
What Are Technical Skills?
Technical skills are the specialized, tool-and-method abilities a role runs on: EHR systems for nurses, CAD for engineers, POS systems for store managers, analytics stacks for marketers, programming languages for developers. They're the deepest subset of hard skills, and every field has them; "technical" describes the skill, not the job title. If a machine, a system, or a method has a name and a learning curve, it belongs in this category.
How to Format Technical Skills on a Resume
Technical skills only help your resume if they are presented in a way that recruiters and ATS software can understand. Before looking through the full list, learn how to choose, format, and support these skills with evidence.
The format that works, first for a clinical resume:
TECHNICAL SKILLS (Clinical Resume)
- Clinical systems: Epic (advanced, 6 yrs), Cerner (proficient), PACS
- Patient tech: Infusion pumps, telemetry monitoring, POC testing
- Documentation: ICD-10 coding (familiar), HIPAA-compliant charting
- Currently learning: Epic Willow (pharmacy module)
And the same skeleton on a data resume:
TECHNICAL SKILLS (Data resume)
- Languages: Python (advanced), SQL (advanced), TypeScript (proficient)
- Data: pandas, dbt, BigQuery, Tableau
- Cloud: AWS (Lambda, S3), Docker, GitHub Actions
- Currently learning: Kubernetes (homelab cluster since March)
To make this format work in any field, keep these four rules in mind:
- Group by category, not alphabet. Categories communicate seniority; a recruiter reads the row labels before the tools.
- Tier your proficiency honestly. Advanced means you could be tested on it today. Proficient means daily working use. Familiar means you've done something real but small with it. Anything below familiar goes in "currently learning" or nowhere.
- Mirror the posting's exact names. The applicant tracking systems that 82% of HR professionals screen with, per our Hiring Landscape survey of 200+ HR pros, match strings: "GA4" and "Google Analytics 4" are different keywords, and so are "Epic" and "EpicCare." Take the ad's spelling the same way you would with any resume keyword.
- Prove the top two in bullets. "Cut chart-closure time 22% by building Epic SmartPhrases for the unit" outranks any skills-line mention of Epic, because impactful resume bullets pair the tool with a result a recruiter can measure instead of just naming it.
Weak Technical Skills
- Skills: GA4, GTM, Ahrefs, Semrush, HubSpot, Marketo, Klaviyo, Meta Ads, Google Ads, Optimizely, Hotjar, WordPress
Strong Technical Skills
- Analytics: GA4 (advanced, 4 yrs), Tag Manager (proficient), Looker Studio (familiar, 3 client dashboards)
Why: twelve bare tools reads as keyword cramming; three tiered ones with receipts reads like someone telling the truth about what they use.*
The AI-Dependency Question
In 2026, interviewers are asking a new question across every field: which technical skills can you still demonstrate without AI assistance?
In our AI Workplace Audit of 1,000 US workers, 27.2% have skills on their resume or LinkedIn they can only perform with significant AI help, rising to 36.8% among Gen Z. Technical skills are where the gap surfaces fastest, because skills tests, live demos, and hands-on assessments are AI-free by design.
The resume fix is disclosure by tiering, not omission: "Financial modeling (advanced), Python for reporting (AI-assisted, 2 automated workflows)" is honest, current, and interview-safe. What breaks careers is the advanced label on an AI-assisted skill. Listing AI skills on a resume works the same way, naming the exact tool and the workflow you run it in so the claim survives a follow-up question.
Put your certifications next to the skill, not in a separate graveyard section at the bottom: "Epic (credentialed, 2025)," "AWS (Solutions Architect Associate, 2025)," "EPA 608 (Universal)." A recruiter scanning the skills block should hit the verification in the same second they hit the claim. For technical roles in any field, I would trade almost any resume real estate for that pairing.
How Many Technical Skills Should You List?
Between 10 and 15 across three or four category rows for most roles, drawn from a master list you tailor per posting. Below 8 reads thin for senior roles; above 20 reads indiscriminate for any role. Entry-level candidates can run shorter rows with a heavier "currently learning" line and lean on certifications for verification.
Examples of Technical Skills Section on Real Resume
150+ Technical Skills by Field
Technical skills look different depending on the industry, role, and level of specialization. Use these categories to find the tools, platforms, and methods most relevant to your career path, then prioritize the ones that match the jobs you are targeting.
#1. Healthcare and Lab
- EHR systems (Epic, Cerner)
- Medical imaging (PACS)
- LIMS
- PCR and assay techniques
- Sterile technique
- Medical device operation
- Infusion pump operation
- Telemetry monitoring
- Point-of-care testing
- Telehealth platforms
- ICD-10 and CPT coding
#2. Engineering and Manufacturing
- AutoCAD
- SolidWorks
- Revit
- MATLAB
- PLC programming
- CNC operation
- 3D printing and rapid prototyping
- GD&T
- FEA analysis
- Lean and Six Sigma
- P&ID reading
- Quality systems (ISO 9001)
#3. Skilled Trades and Field Service
- Blueprint and schematic reading
- HVAC diagnostics
- Electrical troubleshooting (multimeter, insulation testing)
- Welding processes (MIG, TIG, stick)
- Hydraulic and pneumatic systems
- Preventive maintenance planning (CMMS)
- Forklift and aerial lift operation (OSHA-certified)
- Pipefitting and brazing
- Equipment calibration
- Field service platforms (ServiceTitan)
#4. Finance and Business
- Advanced Excel (Power Query, VBA)
- Financial modelling
- Bloomberg Terminal
- SAP
- Oracle NetSuite
- Anaplan
- Power BI for finance
- SQL for reporting
- Alteryx
- Risk modelling
#5. Marketing and E-commerce
- GA4
- Google Tag Manager
- SEO tooling (Search Console, Ahrefs, Semrush)
- Google Ads
- Meta Ads Manager
- Marketing automation (HubSpot, Marketo)
- Email platforms (Klaviyo)
- Attribution modelling
- Landing page testing (Optimizely)
- Shopify administration
#6. Education and Training
- LMS administration (Canvas, Moodle, Google Classroom)
- Student information systems (PowerSchool)
- Assessment platforms (ExamSoft, Kahoot)
- Instructional design tools (Articulate, Captivate)
- Virtual classroom delivery (Zoom, Teams)
- Accessibility and accommodations tech (screen readers, captioning)
- Plagiarism and proctoring tools (Turnitin)
- Classroom AV and smartboards
#7. Retail and Hospitality Operations
- POS systems (Square, Toast, Lightspeed)
- Inventory management (WMS, RFID scanning)
- Property management systems (Opera, Cloudbeds)
- Reservation platforms (OpenTable)
- Merchandising and planogram software
- Payment processing and PCI basics
- Scheduling software (Deputy, 7shifts)
- Loss-prevention systems
#8. Admin and Office Systems
- Advanced Excel (pivot tables, XLOOKUP)
- Calendar and travel management (Outlook, Concur)
- Document management (SharePoint, DocuSign)
- CRM upkeep (Salesforce, HubSpot)
- Expense and invoicing systems (QuickBooks, Expensify)
- Mail-merge and template automation
- Records retention systems
- Videoconferencing and office AV setup
#9. Data and Analytics
- SQL
- pandas and NumPy
- R
- Machine learning (scikit-learn)
- Statistical modelling
- A/B test design
- Tableau
- Power BI
- Looker
- BigQuery
- Snowflake
- dbt
- Airflow
- Data storytelling
#10. Programming and Development
- Python
- JavaScript and TypeScript
- Java
- C#
- C++
- Go
- Rust
- Swift and Kotlin (mobile)
- HTML and CSS
- React
- Node.js
- REST APIs
- GraphQL
- Git and GitHub
- Unit testing
- Agile and Scrum workflow
#11. Cloud and DevOps
- AWS (EC2, S3, Lambda)
- Microsoft Azure
- Google Cloud
- Docker
- Kubernetes
- Terraform
- Ansible
- CI/CD pipelines (GitHub Actions, Jenkins)
- Linux administration
- Monitoring (Datadog, Grafana)
- Serverless architecture
#12. IT Support and Systems
- Windows, macOS, and Linux administration
- Active Directory
- Microsoft 365 admin
- Mobile device management (Intune, Jamf)
- SSO configuration (Okta)
- Ticketing (Zendesk, ServiceNow)
- Hardware diagnostics
- Network troubleshooting (TCP/IP, DNS)
- VPN and endpoint management
- Backup and recovery
- Scripting (PowerShell, Bash)
#13. Cybersecurity
- Network security
- Penetration testing
- SIEM tools (Splunk)
- Vulnerability scanning
- Incident response
- Threat modeling
- Endpoint detection (EDR)
- Identity and access management
- Firewall configuration
- SOC 2 and ISO 27001 compliance
#14. AI and Automation
- Prompt engineering
- LLM API integration (Claude, GPT)
- AI-assisted coding (Copilot)
- Workflow automation (Zapier, Make, n8n)
- RAG basics
- Vector database basics
- AI output evaluation and fact-checking
- Chatbot configuration
- OCR and document AI
#15. Design and Media
- Figma
- Adobe Creative Suite
- After Effects
- Blender
- 3D modeling (Maya)
- Unity and Unreal basics
- Video pipelines (Premiere, DaVinci)
- Webflow and WordPress
- Design systems
- Accessibility testing (WCAG)
#16. Research and Science
- SPSS
- Stata
- LaTeX
- Literature databases (PubMed, Scopus)
- Citation managers (Zotero, EndNote)
- Electronic lab notebooks
- Chromatography (HPLC)
- Mass spectrometry
- Cell culture
- Statistical power analysis
#17. Product and Project
- Jira administration
- Roadmapping tools (Productboard)
- SQL for product analytics
- Amplitude and Mixpanel
- Session analytics (Hotjar)
- API literacy
- Feature flagging (LaunchDarkly)
- Confluence documentation
- Dashboarding (Metabase)
One level below these fields sits the everyday-software layer: the computer skills every role assumes, from office suites to collaboration tools, which follow the same list-then-prove rules.

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Key Takeaways
- Every field has technical skills; name the systems, not the category ("Epic," not "medical software").
- Group skills by category with honest proficiency tiers; the row labels carry the seniority signal.
- Mirror the job ad's exact tool names for the ATS string match.
- Prove your top two skills with quantified bullets; the block gets you found, the bullets get you called.
- Label AI-assisted skills as such; the assessments that expose the gap are AI-free by design.
- Pair certifications inline with the skill they verify.




