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 Data Engineer

Imprint · New York

Who We Are

Imprint is reimagining co-branded credit cards & financial products to be smarter, more rewarding, and truly brand-first. We partner with companies like Crate & Barrel, Rakuten, Booking.com, H-E-B, Fetch, and Brooks Brothers to launch modern credit programs that deepen loyalty, unlock savings, and drive growth. Our platform combines advanced payments infrastructure, intelligent underwriting, and seamless UX to help brands offer powerful financial products—without becoming a bank.

Co-branded cards account for over $300 billion in U.S. annual spend—but most are still powered by legacy banks. Imprint is the modern alternative: flexible, tech-forward, and built for today’s consumer. Backed by Kleiner Perkins, Thrive Capital, and Khosla Ventures, we’re building a world-class team to redefine how people pay—and how brands grow. If you want to work fast, solve hard problems, and make a real impact, we’d love to meet you.

Learn more about us on Imprint's Technology blog.

The Team

The Data Engineering team at Imprint is responsible for building and scaling the data infrastructure that supports product development, analytics, operations, and machine learning across the company. We own the pipelines, platforms, and processes that empower our stakeholders to trust and act on our data.

We’re looking for a Senior Data Engineer to help evolve our modern data stack and deliver reliable, scalable data solutions. Your work will directly power decision-making and innovation across the business—from financial operations to real-time personalization.

What You’ll Do

  • Design, build, and maintain scalable data pipelines and infrastructure across batch and streaming systems.

  • Own core components of Imprint’s data stack, including Snowflake, dbt Cloud, Change Data Capture frameworks, and reverse ETL integrations.

  • Develop and enforce best practices in data modeling, testing, observability, and governance.

  • Partner with stakeholders across Product, Analytics, Finance, and Engineering to ensure timely and accurate data delivery.

  • Work on external data integrations, such as partner-facing data shares (e.g., S3, SFTP, Snowflake) and financial reporting pipelines (e.g., with Netsuite).

  • Contribute to architectural decisions for how we scale data infrastructure, including schema design, orchestration, and data lineage.

  • Champion clear documentation, reproducibility, and reliability for critical datasets and workflows.

  • Stay informed about modern data tools and trends and help drive their adoption when appropriate.

What We Look For

  • 6+ years of experience in data engineering, analytics engineering, or related roles.

  • Expertise in Snowflake and dbt Cloud, with a strong understanding of dimensional modeling and data warehouse best practices.

  • Experience working with Change Data Capture (e.g., Fivetran, Hevo), ETL/ELT pipelines, and orchestration frameworks (e.g., dbt Cloud, Airflow).

  • Familiarity with reverse ETL tools like Hightouch or Segment, and operational analytics use cases.

  • Strong SQL skills and proficiency in Python or a similar programming language.

  • A track record of technical ownership and shipping production-grade data systems.

  • A detail-oriented mindset and a passion for building clean, maintainable, and observable data systems.

  • Strong communication skills and the ability to collaborate effectively with cross-functional partners.

Nice to Have

  • Experience in fintech, high-growth startups, or customer-facing data products.

  • Familiarity with event streaming technologies like Kafka or Kinesis.

  • Exposure to data governance, security, or compliance practices.

  • Previous work on ML pipelines or experimentation frameworks.

Perks & Benefits

  • Competitive compensation and equity packages

  • Leading configured work computers of your choice

  • Flexible paid time off

  • Fully covered, high-quality healthcare, including fully covered dependent coverage

  • Additional health coverage includes access to One Medical and the option to enroll in an FSA

  • 20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents

  • Access to industry-leading technology across all of our business units, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity

Imprint is committed to a diverse and inclusive workplace. Imprint is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Imprint welcomes talented individuals from all backgrounds who want to build the future of payments and rewards. If you are passionate about FinTech and eager to grow, let’s move the world forward, together.