Key Takeaways

  • 75% of U.S. employers use automated applicant tracking systems to screen resumes before a human reviews them (Harvard Business School & Accenture, 2021)
  • The most common ATS failures are missing keywords, incompatible formatting, and incorrect file types
  • ResumeGeni scores your resume across 8 parsing layers — modeled on the same steps enterprise ATS platforms like Workday, Greenhouse, and Taleo use to evaluate candidates

How ATS Resume Scoring Works

Applicant tracking systems parse your resume into structured data — extracting your name, contact info, work history, skills, and education — then score how well that data matches the job requirements. Many ATS rejections happen because the parser couldn't extract critical fields, not because the candidate wasn't qualified.

LayerWhat It ChecksWhy It Matters
Document extractionFile format, encoding, readabilityCorrupted or image-only PDFs fail immediately
Layout analysisTables, columns, headers, footersMulti-column layouts break field extraction
Section detectionExperience, education, skills headingsNon-standard headings cause sections to be missed
Field mappingName, email, phone, dates, titlesMissing contact info is a common cause of immediate rejection
Keyword matchingJob-specific terms, skills, certificationsKeyword overlap affects recruiter search visibility and ATS scoring
Chronology checkDate ordering, gap detectionReverse-chronological order is expected by most ATS
QuantificationMetrics, numbers, measurable outcomesQuantified achievements help human reviewers and some scoring models
Confidence scoringOverall parse quality and completenessLow-confidence parses get deprioritized in results

Frequently Asked Questions

Is ResumeGeni free?
Yes. ResumeGeni is currently in beta — ATS analysis, scoring, and initial improvement suggestions are free with no signup required. Full guidance and saved reports may require a free account.
What file formats are supported?
PDF, DOCX, DOC, TXT, RTF, ODT, and Apple Pages. PDF and DOCX are recommended for best ATS compatibility.
How is the ATS score calculated?
Your resume is processed through an 8-layer parsing pipeline that extracts structured data the same way enterprise ATS platforms do. The score reflects how completely and accurately your resume can be parsed, plus how well your content matches common ATS ranking criteria.
Can ATS read PDF resumes?
Yes, but not all PDFs are equal. Text-based PDFs parse well. Image-only PDFs (scanned documents) and PDFs with complex tables or multi-column layouts often fail ATS parsing. Our analyzer will flag these issues.
How do I improve my ATS score?
Focus on three areas: use a clean single-column format, include keywords from the job description naturally in your experience bullets, and ensure all sections (contact, experience, education, skills) use standard headings.

ATS Guides & Resources

Built by engineers with 12 years of experience building enterprise hiring technology at ZipRecruiter. Last updated .

Senior Airflow Reliability Engineer - Hyderabad

Astronomer · Hyderabad

Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading unified DataOps platform powered by Apache Airflow®. Astro accelerates building reliable data products that unlock insights, unleash AI value, and powers data-driven applications. Trusted by more than 800 of the world's leading enterprises, Astronomer lets businesses do more with their data. To learn more, visit www.astronomer.io.

About this role:

As an Airflow Reliability Engineer on the Customer Reliability Engineering (CRE) team at Astronomer, you will have the opportunity to become an Apache Airflow expert, learning directly from leaders of the Airflow project. You’ll provide Apache Airflow expertise directly to customers to help them make the best possible use of our managed Airflow service.

CRE is Astronomer’s support team. Because our customers are sophisticated organizations who need and expect high levels of expertise to help them keep mission critical uses of Apache Airflow working consistently, we look a little different from most support teams. Nearly every ticket you will work requires an intersection of strong technical knowledge and customer empathy to understand what the customer needs and how to get them there. Every day is a new challenge and a new thing to learn.

When you learn a new piece of technology, are you aiming not just to get started but to become the expert? Do you listen to the plumber when they tell you what is wrong with the pipes? Are you the kind of person who takes an MIT OpenCourseWare course and actually finishes it? Then this role could be for you.

This is a hybrid role based in Hyderabad that requires working in shifts, typically early mornings or evenings IST. The exact schedule will be finalized during the hiring process.

What you get to do:

  • Learn and build expertise across several software engineering disciplines, including:

  • Airflow and data engineering

  • Kubernetes

  • Cloud Engineering

  • Gain exposure to the big picture; learn about product, engineering, customer relationship management, and more.

  • Solve challenging Airflow problems for our customers. From optimizing configuration to identifying world-first Airflow bugs, you’ll see it all here.

  • Spend up to 25% of your time on side projects that contribute to Astronomer’s overall success, such as contributing to the open-source Airflow repository or developing Astronomer’s internal monitoring and alerting systems built on Airflow.

  • Work on a modern, sophisticated, cloud-native product that customers use to connect to dozens of other systems. Gain depth and breadth of learning!

  • Work directly with our customers’ data engineers, system admins, DevOps teams, and management.

  • Provide feedback from your experience that can shape the direction of the Airflow project.

  • Own the customer experience, working directly with customers to prioritize and solve issues, meet SLAs, and provide “white glove” guidance on the path to production.

  • Participate remotely within a fully distributed team.

  • Help maintain 24x7 coverage through a specified 6-hour pager period during your work day.

  • Participate in paid on-call rotation for weekend coverage.

What you bring to the role:

  • Data Engineering background

  • 4 years of experience with Python

  • 1 year of experience with Kubernetes/Docker/Containers

  • Experience in Airflow administration and DAG creation

  • Experience working with a distributed system with any major cloud provider (AWS, GCP, Azure)

  • Problem-solving and troubleshooting abilities

  • Ability to work well with autonomy and independence

  • Strong written and verbal communication for connecting with our customers over our ticketing system and through Zoom

  • Experience mentoring junior team members

Bonus points if you have:

  • Contributions to open-source projects

  • Customer Support experience

  • Familiarity with SQL and PostgreSQL

  • Experience with Databricks, Snowflake, Redshift, dbt, or other similar data engineering tools


#LI-Fulltime

#LI-Hybrid

At Astronomer, we value diversity. We are an equal opportunity employer: we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.