Technical Resume Writing

Input: Current resume + target job description Output: ATS-optimized, quantified technical resume

BEFORE: "Analyzed data and created reports"
AFTER: "Built SQL-based reporting dashboards in Tableau, enabling leadership to track 15+ KPIs and improve quarterly revenue forecasting accuracy by 28%"

Progress:

• Collect current resume, target job descriptions, and career goals
• Research target role requirements and industry trends
• Reverse-engineer job descriptions for keywords and competencies
• Analyze resume gaps against role requirements
• Rewrite content using STAR/CAR framework with quantified results
• Apply ATS/AI optimization techniques
• Format with ATS-safe structure
• Validate using ATS scoring tools
• Review with client and incorporate feedback

1. Job Description Reverse Engineering

Extract from target job postings:

• Core technical skills and tools
• Required frameworks/methodologies
• Business outcomes and responsibilities
• Create keyword/competency map

2. Resume Gap Analysis

Compare current resume to requirements:

• Missing technical skills
• Weak or outdated terminology
• Under-quantified achievements
• Misaligned job titles

3. Content Optimization

Rewrite using:

• Action verbs: Built, automated, optimized, implemented
• Technical specificity: "SQL-based dashboards" not "reports"
• STAR format: Situation-Task-Action-Result
• Quantified impact: Percentages, timelines, scale

4. ATS/AI Optimization

• Match semantic keywords naturally
• Use role-standard job titles
• Expand acronyms: "CI/CD (Continuous Integration/Continuous Deployment)"
• Maintain 2-3% keyword density
• Use bias-free, inclusive language

Example 1 - Data Analyst: Input: "Used Python for data analysis" Output: "Developed automated data pipelines using Python and pandas, processing 10M+ records daily and reducing manual analysis time by 65%"

Example 2 - Software Engineer: Input: "Built web applications" Output: "Architected and deployed React/Node.js microservices handling 50K+ daily active users with 99.9% uptime using AWS ECS and Docker"

Example 3 - DevOps Engineer: Input: "Managed infrastructure" Output: "Designed Terraform-based infrastructure-as-code solutions on AWS, reducing deployment time from 4 hours to 15 minutes and eliminating manual configuration errors"

Technical Skills Section:

• Group by category: Languages, Frameworks, Cloud Platforms, Databases
• List versions for major tools: "Python 3.9+", "AWS (EC2, S3, Lambda)"
• Match job description terminology exactly

Achievement Quantification:

• Performance metrics: response time, throughput, uptime
• Business impact: cost savings, revenue increase, user growth
• Scale indicators: data volume, user count, system capacity
• Time savings: automation benefits, process improvements

ATS Formatting:

• Use standard section headers: "Professional Experience", "Technical Skills"
• Avoid tables, graphics, or complex formatting
• Use consistent date formats: "Jan 2023 – Present"
• Save as .docx and .pdf versions

Don't:

• Use generic phrases like "responsible for" or "worked on"
• List every technology you've touched briefly
• Ignore the job description's specific terminology
• Over-optimize with keyword stuffing
• Use creative formatting that breaks ATS parsing
• Forget to tailor for each application

Avoid these weak phrases:

• "Familiar with" → "Experienced in"
• "Helped with" → "Led" or "Contributed to"
• "Various technologies" → List specific tools
• "Improved performance" → "Improved response time by 40%"