As a data analyst, your CV needs to demonstrate your ability to turn data into insights and drive business decisions. In 2026, with data roles in high demand across every industry, having a well-structured, ATS-optimized resume is essential for landing interviews at companies that rely on data-driven decision-making.

The best data analyst CVs follow a specific formula: they highlight technical skills (SQL, Python, visualization tools), quantify analytical impact, and pass Applicant Tracking Systems (ATS) that screen the majority of resumes before a human ever sees them.

This guide provides you with a free, ATS-friendly data analyst CV template for 2026, complete with examples, best practices, and actionable tips. Whether you're a junior analyst or a senior data professional, you'll learn exactly how to structure your resume to land interviews.

Data analyst resumes are different from other roles. Recruiters and hiring managers look for specific elements:

• •Technical Skills: SQL, Python, R, Excel, and visualization tools (Tableau, Power BI, Looker) must be clearly listed
• •Quantified Impact: Metrics on reporting efficiency, accuracy improvements, and business outcomes are crucial
• •Analytical Projects: Dashboards, reports, and data pipelines demonstrate practical experience
• •ATS Compatibility: Most companies use ATS systems that require specific formatting
• •Domain Knowledge: Industry context (finance, marketing, operations) strengthens your profile

1. Header Section

Your header should include:

• •Full name (prominent, professional font)
• •Professional title: "Data Analyst" or "Senior Data Analyst"
• •Email address (professional)
• •Phone number (with country code if applying internationally)
• •Location (City, Country - optional for remote roles)
• •LinkedIn profile URL
• •GitHub or portfolio (if you have data projects)

2. Professional Summary (3-4 sentences)

Your summary should immediately communicate your value. For data analysts, include:

• •Years of experience in data analysis
• •Key tools and technologies (SQL, Python, Tableau, etc.)
• •Domain expertise (e.g. marketing analytics, finance, operations)
• •Quantified achievements or impact

3. Technical Skills Section

Organize skills by category:

• •Languages & Query: SQL, Python, R, Excel (advanced)
• •Visualization: Tableau, Power BI, Looker, Google Data Studio
• •Analysis: Statistical analysis, A/B testing, forecasting, cohort analysis
• •Data & Tools: ETL, data modeling, dbt, Snowflake, BigQuery, Redshift
• •Domain: Marketing analytics, finance, operations, product analytics

Pro Tip 2026: List skills in order of relevance to the job. If the role emphasizes Python and Tableau, put those first.

4. Work Experience

For each role, include:

• •Job title
• •Company name
• •Location and employment dates
• •3-5 bullet points with quantified analytical impact

What Makes Great Data Analyst Experience Bullets:

• •Quantified impact: "Built SQL-based reporting that reduced manual report time by 60%"
• •Business outcomes: "Analysis identified $500K in cost savings opportunities"
• •Scale: "Created dashboards used by 200+ stakeholders"
• •Technical detail: "Developed Python pipelines for automated data quality checks"

5. Projects (Recommended)

Especially valuable for junior analysts or career changers. Include project name, tools used, and outcome.

6. Education

Include degree, field of study, university, graduation year. Relevant coursework or thesis can strengthen your profile.

7. Certifications (Optional)

Google Data Analytics, Microsoft Power BI, Tableau, or domain certifications (e.g. CFA for finance) add credibility.

Junior Data Analyst (0-2 years)

Emphasize: education, coursework, internships, personal or academic projects, technical skills, and eagerness to learn.

Mid-Level Data Analyst (2-5 years)

Highlight: quantified impact, dashboards and reports delivered, tools mastered, and cross-functional collaboration.

Senior Data Analyst (5+ years)

Emphasize: strategic impact, mentoring, complex analyses, and ownership of data products or reporting frameworks.

In 2026, most companies use ATS systems. Ensure your data analyst CV passes by:

• •Using standard section headings: "Work Experience," "Education," "Skills"
• •Including keywords from the job description (tools, methodologies, domain)
• •Using simple, clean formatting—no graphics or complex tables
• •Saving as PDF and naming: FirstName_LastName_DataAnalyst_CV.pdf

• •Listing every tool you've touched: Focus on tools you use well and that match the job
• •Vague bullets: Use numbers—"Improved reporting" → "Reduced report build time by 40% with automated SQL"
• •Missing business context: Always tie analysis to business impact (revenue, cost, efficiency)
• •Too long: Aim for 1-2 pages; senior analysts can use 2 pages
• •Generic summary: Replace with a targeted professional summary that matches the role

Our free data analyst CV template for 2026 is:

• •✅ ATS-optimized and tested
• •✅ Compatible with all major ATS systems
• •✅ Professional and modern design
• •✅ Easy to customize
• •✅ Includes all essential sections
• •✅ Optimized for 2026 hiring standards

How long should a data analyst CV be?

For junior analysts: 1 page. For mid-level and senior: 1-2 pages. Prioritize relevance and impact over length.

Should I include a photo?

No. In most countries (US, UK, Canada), photos are not recommended and may be stripped by ATS. Focus on skills and impact.

What tools should I list first?

List tools in order of relevance to the job description. SQL and a visualization tool (Tableau or Power BI) are usually essential; then add Python, R, or domain-specific tools.

Should I include my GPA?

Only if 3.5+ or if you're a recent graduate (within 2 years). For experienced analysts, impact matters more than GPA.

Can I use a creative CV design?

Generally no. Most companies use ATS that require simple, text-based formats. Use a clean, ATS-friendly template.

Continue improving your data analyst CV with these related guides:

• •Free Software Engineer CV Template 2026 - Similar tech-focused template structure
• •Free Product Manager CV Template 2026 - Template for cross-functional roles
• •Best Resume Format in 2026 (ATS-Friendly) - Which format works best for ATS
• •How to Tailor Your CV to a Job Description - Customize your CV for each application
• •ATS Resume Explained: What Recruiters Actually See - How ATS systems work

Creating a winning data analyst CV doesn't have to be complicated. With the right template and structure, you can create a resume that passes ATS and impresses hiring managers.

Our AI-powered CV Tailoring Tool can help you create and optimize your data analyst CV in under 60 seconds. Upload your existing resume, and our AI will tailor it to any job description while keeping ATS compatibility.

You can also use our Free Resume Checker to analyze your CV for ATS compatibility, content quality, and design before you apply.