The two biggest mistakes we see with software skills on resumes? Listing everything you’ve ever touched, and not matching the terminology from the job description. Both will get you filtered out.
This guide covers how to figure out which skills to list, how to format your skills section, and how to prove your proficiency through your experience bullets. We’ll focus on tech and data roles, but the principles apply broadly.
Recruiters aren’t scanning your resume to see how many tools you’ve heard of. They’re looking for specific skills that match what the team needs right now. Listing 20 tools you used once in a bootcamp three years ago doesn’t help. It actually hurts, because it buries the skills that matter under noise.
A useful way to think about it: every role has foundational skills and differentiating skills.
Foundational skills are table stakes. For a data analyst, that’s SQL, Python, Excel, and a visualization tool like Tableau. For a PM, it’s Jira and Figma. You need these to get past the initial screen. If the job description lists them, they need to be on your resume in the exact same language.
Differentiating skills are what set you apart from the other 200 applicants who also listed SQL. Knowing Snowflake, dbt, or a specific cloud platform signals that you have modern, hands-on experience, not just textbook knowledge. These are often what push you from “qualified” to “interview.”
The key: 92% of data jobs list SQL as a requirement. Listing “SQL” alone doesn’t make you stand out. Listing “PostgreSQL” and “Snowflake” alongside it tells a much more specific story about what you’ve actually worked with.
Your instinct will be to list every tool you know. Fight that instinct. Instead, let the job descriptions tell you what matters.
Pull up 3-5 job descriptions for the kind of role you want. Copy every software tool, language, and platform mentioned into a list. You’ll see patterns fast: some tools show up in every posting (those are your foundational skills), others appear in the more interesting or senior roles (those are your differentiators).
This is tedious to do manually, so we built a free prompt that does it for you. Paste in a few job descriptions and it creates a prioritized skills list ranked by how often each one appears. Saves an hour of spreadsheet work.
Here’s what the research typically surfaces for common tech roles:
| Role | Foundational | Differentiating |
|---|---|---|
| Data Analyst | SQL, Python, Tableau, Excel | Snowflake, dbt, Looker, AWS |
| Product Manager | Jira, Figma, Asana | Mixpanel, Pendo, Amplitude, SQL |
| Marketing Manager (Fintech) | HubSpot, Salesforce, Google Analytics | Marketo, SEMrush, Tableau |
This is where people lose interviews without knowing it. If the job description says “Salesforce Marketing Cloud,” don’t write “CRM software.” If it says “Python,” don’t write “scripting languages.” ATS systems match on specific terms, and recruiters skim for the exact keywords they put in the posting.
We see this constantly when resumes come through Proficiently. Someone has the right experience but describes it in their own words instead of the employer’s words. Their resume says “data visualization” when the posting says “Tableau.” It’s the same skill, but the ATS doesn’t know that, and the recruiter scanning 200 resumes in an afternoon might miss it too.
Once you know which skills to list, sort them honestly:
Don’t put familiar skills in your main skills section without context. If Python is critical for the role and you’re still learning it, list it under “Currently Learning” with the course or project you’re working on: “Python (Coursera Specialization in Progress).” This is honest and shows initiative. Claiming expertise you don’t have will blow up in a technical screen.
Your skills section has two audiences: the ATS parsing it into structured fields, and the recruiter scanning it for 10 seconds. Both need it to be clean, specific, and organized.
If you’re using a Canva template with skill bars or star ratings, those need to go. They’re less common than they used to be, but we still see them. ATS systems can’t read graphics, so a five-star rating next to Python is literally invisible to the software. And for humans, “four out of five stars” in SQL is meaningless. Your four stars and the next candidate’s four stars could mean completely different things.
Let your experience bullets prove your proficiency. That’s more convincing than any rating system.
Instead of one long list, organize your skills under clear subheadings:
This helps the ATS categorize your skills correctly and lets a recruiter find what they’re looking for in seconds. For more on structuring your resume for ATS, check out our guide on ATS-friendly resume templates.
The difference between a weak and strong skills section is almost always specificity.
Weak:
Strong:
The strong version uses the exact tool names that appear in job descriptions, adds context about depth of knowledge, and doesn’t waste space on skills everyone has.
For technical roles, go even deeper:
Weak:
Strong:
Listing specific services, libraries, and features tells the story of someone who actually uses these tools, not someone who read the Wikipedia page.
A skills section tells people what you know. Your experience bullets prove it. The skills section gets you past the ATS; the bullets are what make a recruiter pick up the phone.
For each bullet point, try: [Action] + [what you did] using [specific tool] → [measurable result]
This connects the software to a business outcome. Listing “Tableau” in your skills section says you know the tool. Writing “Automated weekly performance reports using Tableau and SQL, reducing manual data compilation by 10 hours per week” proves you used it to solve a real problem.
Data Analyst:
Product Manager:
Marketing Specialist:
Finance Analyst:
Notice the pattern: every “after” version names the specific software, describes what you did with it, and attaches a number to the result. That’s the formula. Use it for every bullet that involves a tool.
Now, the honest reality: doing this well for every bullet on every application takes real effort. When you’re tailoring your resume for 15-20 applications a week, rewriting experience bullets to match each job’s specific tool requirements is one of the most time-consuming parts. This is one of the things Proficiently handles for you. When you approve a job, we rewrite your resume to match that specific posting, including pulling the right skills into the right spots.
If you’re switching into tech from another field, you probably can’t point to years of professional Python experience. That’s fine. The key is proving you can do the work, even if you learned the tools outside a traditional job.
Build something. A certificate from a bootcamp is nice, but a project is proof. Find a public dataset, analyze it in Python, visualize it in Tableau, and put it on GitHub. Now you have a concrete thing to reference in your bullet points.
Frame your past experience as a bridge. A finance analyst who built complex Excel models has a proven aptitude for data work. Write it that way: “Analyzed datasets of 50,000+ rows using advanced Excel modeling, building a foundation for transitioning to Python and SQL-based analysis.”
Add a “Projects” section to your resume with links. This gives recruiters something tangible to evaluate and shows initiative. For more on this approach, check out our guide on transferable skills for career change.
At the VP or executive level, nobody cares if you can personally write SQL. They care whether you can build and lead a team that uses technology effectively.
Frame your skills around strategic decisions and outcomes:
These bullets show you understand how technology drives business results, which is what the hiring committee actually wants to hear.
For most tech roles, yes. Basic Office proficiency is assumed. It’s like listing “email” as a skill. Every line on your resume should earn its spot, and “Microsoft Office” pushes more relevant tools further down the page.
Two exceptions: if the job explicitly requires it (include it to pass the ATS filter), or if you have genuinely advanced Excel skills — VBA, Power Pivot, financial modeling. In that case, list “Advanced Excel (VBA, Power Pivot, Financial Modeling)” because that’s a different skill entirely.
Aim for 5-7 skills directly relevant to the job. A curated short list beats a long one every time. When a recruiter sees 20 tools listed, they wonder whether you’re really proficient in any of them. A focused list of 6 tools that exactly match the job description signals that you read the posting and know what matters.
Tailoring this list for each application is one of the highest-leverage things you can do. It takes a few minutes per application and the return is real. If you want that done automatically, that’s part of what Proficiently does — when you approve a job, we tailor the entire resume including the skills section.
Put them in a separate section labeled “Currently Learning” or “Professional Development.” Include the course or project: “Python (Coursera Specialization in Progress).” If it’s a critical skill for the role, build a small project with it and link to your GitHub. That turns “I’m learning this” into “here’s proof I can use it.”
Never list a skill you’re still learning in your main tech stack without this context. You’ll get caught in a technical screen and it’ll cost you the role.
No. ATS can’t read them (your most important skills become invisible to the software), and humans find them meaningless. Your four stars in SQL tells a recruiter nothing about what you actually know. Prove your proficiency through your experience bullets instead. “Built automated reporting pipeline using SQL and Python” is worth more than any star rating.
Proficiently is a personal job search agent. You tell us what roles you want, we find the matches, and when you approve one, we tailor your resume — skills section, experience bullets, everything — to that specific job and submit the application. You pick the jobs. We handle the rest.
