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 .

Staff Software Engineer - Backend

Databricks · Vancouver, Canada

Databricks is on a mission to simplify and democratize data and AI — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.  

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

  • Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.
  • AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack. 
  • Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.
  • Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

  • BS (or higher) in Computer Science, related technical field or equivalent practical experience.
  • Comfortable working towards a multi-year vision with incremental deliverables.
  • Motivated by delivering customer value and impact.
  • 10+ years of production level experience in either Java, Scala or C++.
  • Strong foundation in algorithms and data structures and their real-world use cases.
  • Experience developing large-scale distributed systems.
  • Experience working on a SaaS platform or with Service-Oriented Architectures.
  • Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
  • Experience with security and systems that handle sensitive data.
  • Good knowledge of SQL.

 

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticpates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. 

 

Canada Pay Range
$173,400—$238,350 CAD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. 

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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