How to Apply to Datadog

Key Takeaways

Datadog is a high-growth, engineering-driven company with over 450+ open roles — tailor your application to the specific team and product area you're targeting
The company uses Greenhouse as its ATS, so ensure your resume is cleanly formatted, keyword-optimized, and fully parsed by submitting in a standard PDF format
Technical depth matters across all roles at Datadog — even non-engineering positions benefit from demonstrating comfort with cloud infrastructure, DevOps concepts, and observability tools
Quantify your impact wherever possible: metrics on scale, revenue, efficiency gains, or user outcomes will resonate strongly with Datadog's data-driven culture
Prepare thoroughly for a multi-round interview process that evaluates both hard skills and cultural alignment — ownership, curiosity, and communication are recurring themes
Familiarize yourself with Datadog's product suite before applying — understanding the difference between infrastructure monitoring, APM, log management, and newer AI observability features shows genuine interest and preparation
For sales and GTM roles, emphasize experience in the cloud/SaaS/DevOps ecosystem and your ability to engage with highly technical buyers and stakeholders

About Datadog

Datadog is a leading cloud-scale monitoring and analytics platform that provides comprehensive observability across an organization's entire technology stack — including infrastructure, applications, logs, and security. Founded in 2010 and publicly traded on NASDAQ (DDOG), the company has grown into one of the most prominent players in the observability and cloud monitoring space, serving thousands of enterprise customers worldwide. Datadog is commonly recognized for its engineering-driven culture, rapid product innovation, and commitment to solving complex problems at massive scale. The company competes alongside platforms like Splunk, New Relic, and Dynatrace, but has differentiated itself through a unified platform approach and aggressive expansion into areas like AI observability, security monitoring, and application performance management. With over 450+ open openings spanning engineering, sales, product, design, and operations, Datadog is in a significant growth phase. The company's culture is often described as fast-paced, technically rigorous, and collaborative, with a strong emphasis on ownership, data-driven decision-making, and continuous learning.

Application Process

1
Explore Open Roles on the Datadog Careers Page
Begin by visiting Datadog's official careers page at careers.datadoghq.com. With over 450+ open positions across engineering, sales, product, design, customer success, and operations, it's important to filter roles by department, location, and seniority level. Datadog posts roles across global offices including New York, Paris, Dublin, Singapore, Sydney, and remote locations. Take time to read each job description thoroughly — Datadog tends to be specific about required technical skills, experience levels, and team context. Note the team the role sits within (e.g., ML Observability, AI Observability, Custom Metrics) as this will help you tailor your application materials.
2
Submit Your Application Through Greenhouse
Datadog uses Greenhouse as its applicant tracking system (ATS). When you click 'Apply' on a job listing, you'll typically be directed to a Greenhouse-powered application form. You'll be asked to upload your resume, provide contact information, and may encounter role-specific questions or optional fields for a cover letter and LinkedIn profile. Ensure your resume is in a clean, ATS-friendly format (PDF or Word) and that all fields are completed accurately. Some roles may also ask for links to portfolios, GitHub profiles, or relevant work samples — have these ready before starting your application.
3
Initial Recruiter Screen
If your application passes the initial review, many applicants report being contacted by a Datadog recruiter for a phone or video screening. This conversation typically lasts 30-45 minutes and covers your background, motivation for applying, understanding of Datadog's products, and basic qualifications for the role. For technical roles, the recruiter may ask high-level questions about your experience with relevant technologies. For sales and go-to-market roles, expect questions about your track record, deal sizes, and familiarity with the cloud/SaaS ecosystem. This is also your opportunity to ask about team structure, growth trajectory, and the interview timeline.
4
Technical or Functional Assessment
Following the recruiter screen, candidates commonly move to a more in-depth assessment phase. For software engineering roles, this typically involves one or more technical interviews that may include coding challenges, system design discussions, or take-home assignments. Staff-level engineering roles often emphasize architecture and scalability thinking. For sales engineering positions, you may be asked to deliver a technical demo or presentation. Product managers and designers may face case studies or portfolio reviews. Sales roles often include mock discovery calls or deal strategy exercises. The format varies by team, but Datadog is known for evaluating both depth of expertise and the ability to communicate complex ideas clearly.
5
On-Site or Virtual Interview Loop
The final stage typically involves a comprehensive interview loop with multiple team members. This commonly includes 4-6 sessions over a half-day or full-day format, conducted either on-site at a Datadog office or virtually. Expect a mix of technical deep-dives, behavioral interviews, and cross-functional conversations. Datadog interviewers often assess cultural fit alongside technical ability — they tend to look for candidates who demonstrate ownership, intellectual curiosity, and the ability to thrive in a fast-paced environment. For leadership roles (e.g., Manager, Sales Development), expect sessions focused on management philosophy, team-building, and strategic thinking.
6
Offer and Negotiation
Candidates who successfully complete the interview loop may receive an offer from Datadog's recruiting team. Offers typically include competitive compensation packages that may encompass base salary, equity (RSUs), bonuses, and comprehensive benefits. Many applicants report that Datadog's recruiters are responsive and transparent during the offer stage. If you receive an offer, take time to evaluate the full package, ask clarifying questions about equity vesting schedules and benefits, and negotiate respectfully if appropriate. Datadog's strong market position and public company status generally mean well-structured compensation frameworks.

Resume Tips for Datadog

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Emphasize Scale and Complexity

Datadog operates at massive cloud scale, processing trillions of data points daily. Your resume should highlight experience working with large-scale distributed systems, high-throughput data pipelines, or enterprise-grade platforms. Use specific metrics — for example, 'Designed a monitoring pipeline processing 500M events/day' or 'Managed infrastructure serving 10K+ concurrent users.' Even for non-engineering roles, demonstrating comfort with technical complexity and scale is valuable, as Datadog's products are deeply technical.

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Align Keywords with Job Descriptions

Since Datadog uses Greenhouse, which supports keyword-based filtering and structured evaluation, it's important to mirror the language used in the job posting. If a role mentions 'ML Observability,' 'Kubernetes,' 'APM,' or 'cloud-native architectures,' ensure these terms appear naturally in your resume where they reflect genuine experience. For sales roles, include terms like 'enterprise sales cycle,' 'technical discovery,' 'SaaS,' and 'cloud infrastructure.' This alignment helps both automated screening and human reviewers quickly identify your relevance.

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Showcase Product Intuition and Customer Empathy

Datadog is a product-led company that ships features rapidly. For product management, design, and customer success roles, your resume should demonstrate a strong track record of understanding user needs and translating them into impactful product decisions. Include examples of user research, A/B testing, feature launches, and measurable outcomes. Even for engineering roles, showing that you think about the end-user experience can set you apart — Datadog engineers are commonly expected to have strong product sense.

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Quantify Business Impact for GTM Roles

For sales, sales engineering, customer success, and strategy/operations roles, Datadog values candidates who can demonstrate measurable business impact. Include specific numbers: revenue generated or influenced, deal sizes, quota attainment percentages, customer retention rates, or pipeline growth metrics. For a role like 'Strategic Account Executive,' showing a track record of closing six- or seven-figure enterprise deals in the cloud/DevOps space is highly relevant. For 'Business Value Manager' roles, highlight experience building ROI frameworks or conducting value assessments.

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Use a Clean, ATS-Compatible Format

Avoid complex formatting, tables, multi-column layouts, headers/footers with critical information, or embedded images that Greenhouse's parser may not read correctly. Stick to standard section headings like 'Experience,' 'Education,' 'Skills,' and 'Projects.' Use a professional, readable font and consistent formatting. Submit as a PDF unless the application specifically requests another format. Ensure your name and contact information appear in the main body of the document, not solely in headers.

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Highlight Relevant Domain Knowledge

Datadog's product suite spans infrastructure monitoring, APM, log management, security, CI/CD visibility, and increasingly AI/ML observability. If you have experience with observability tools, DevOps practices, cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), or related technologies, make this prominent on your resume. For AI-focused roles like 'Staff Product Designer - AI Observability,' emphasize any experience with ML workflows, LLM monitoring, or AI infrastructure.

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Include Open Source Contributions or Side Projects

Datadog has a strong engineering culture and contributes to open-source projects. If you've contributed to open-source monitoring tools, observability frameworks, or related projects, include these on your resume with links. Personal projects that demonstrate technical depth — especially in areas like distributed tracing, metrics collection, or data visualization — can help differentiate your application for engineering and product roles.

ATS System: Greenhouse

Greenhouse is a widely-used applicant tracking system that helps companies manage their entire hiring pipeline from job posting through offer. When you apply to Datadog, your application is processed through Greenhouse, which parses your resume, organizes your information into a candidate profile, and enables recruiters and hiring managers to evaluate applications using structured scorecards. Greenhouse supports keyword searching, custom application questions, and collaborative evaluation workflows. Understanding how Greenhouse works can help you optimize your application for both automated parsing and human review.

Use standard resume section headings (Experience, Education, Skills) that Greenhouse's parser can reliably identify and categorize correctly.
Avoid placing critical information like your name, email, or phone number exclusively in document headers or footers, as Greenhouse's parser may not extract text from these areas.
Submit your resume as a PDF with selectable text (not a scanned image) to ensure accurate parsing. Avoid heavily designed resumes with tables, columns, or graphics that may confuse the parser.
Complete all required and optional fields in the application form — Greenhouse allows recruiters to filter candidates by completeness, and leaving fields blank may reduce your visibility.
Mirror key terminology from the job description in your resume, as Greenhouse enables recruiters to search candidate pools using specific keywords related to skills, tools, and qualifications.
If the application includes a field for a cover letter or additional information, use it strategically to explain your specific interest in Datadog and the role — this content is visible to reviewers alongside your resume.

Complete Greenhouse Resume Guide →

Interview Culture

Datadog's interview process is commonly described as thorough, technically rigorous, and well-structured.

The company places a strong emphasis on hiring individuals who combine deep technical expertise with strong communication skills and a genuine passion for building products that solve real problems for developers and operations teams. For engineering roles, candidates typically report multiple rounds that assess coding proficiency, system design thinking, and the ability to reason about trade-offs in distributed systems. Staff-level and senior engineering interviews often go deeper into architecture, mentorship philosophy, and cross-team collaboration. Datadog's engineering culture values pragmatism — interviewers commonly look for candidates who can balance theoretical knowledge with practical, production-ready thinking. For go-to-market roles (sales, sales engineering, customer success), the interview process tends to be equally structured but focuses on domain expertise, consultative selling ability, and technical credibility. Sales engineers may be asked to deliver live product demonstrations, while account executives might walk through deal strategies or account plans. The ability to articulate complex technical concepts to diverse audiences is a commonly valued trait. Behaviorally, Datadog interviewers often explore themes of ownership, initiative, and adaptability. Many candidates report being asked about situations where they navigated ambiguity, drove projects without explicit direction, or learned new technologies quickly. The company's rapid growth means they typically seek people who are comfortable with change and can operate effectively in a fast-evolving environment. Overall, candidates frequently describe the process as challenging but fair, with interviewers who are engaged, knowledgeable, and genuinely interested in understanding each candidate's strengths and potential contributions to the team.

What Datadog Looks For

Deep technical expertise relevant to the role — whether in software engineering, cloud infrastructure, machine learning, product design, or enterprise sales
Strong ownership mentality and the ability to drive projects forward with minimal hand-holding in a fast-paced environment
Intellectual curiosity and a genuine passion for understanding how complex systems work, particularly in the observability and cloud-native ecosystem
Excellent communication skills — the ability to explain complex technical concepts clearly to both technical and non-technical audiences
Experience operating at scale, whether that means large-scale distributed systems, high-volume enterprise sales pipelines, or global customer portfolios
Data-driven decision-making and a track record of using metrics and evidence to inform strategy and prioritization
Collaborative mindset with the ability to work effectively across engineering, product, design, sales, and customer success teams
Adaptability and comfort with ambiguity — Datadog's rapid growth and expanding product surface area mean priorities can shift quickly

Frequently Asked Questions

What ATS does Datadog use for job applications?

Datadog uses Greenhouse as its applicant tracking system. When you apply through their careers page at careers.datadoghq.com, your application is processed through Greenhouse, which parses your resume and creates a candidate profile. To optimize your application, use a clean resume format, standard section headings, and include relevant keywords from the job description.

How many open positions does Datadog typically have?

Datadog is actively hiring across many departments. As of the latest available data, the company has approximately 450+ open positions spanning engineering, sales, product management, design, customer success, operations, and more. Roles are available across global offices and some remote locations, reflecting the company's continued growth trajectory.

What types of engineering roles does Datadog hire for?

Datadog hires across a wide range of engineering disciplines, including backend, frontend, infrastructure, machine learning, security, and platform engineering. Recent openings include specialized roles like Staff Software Engineer - ML Observability, reflecting the company's expansion into AI and ML monitoring. Engineering roles at Datadog typically require strong fundamentals in distributed systems, data processing, and cloud-native technologies.

Does Datadog hire for sales and go-to-market roles?

Yes, Datadog has a significant number of sales and go-to-market openings, including Strategic Account Executives, Enterprise Sales Engineers, Sales Development Managers, Customer Success Associates, and Business Value Managers. These roles span multiple regions and market segments. Candidates with experience selling or supporting technical SaaS products in the cloud infrastructure, DevOps, or observability space are typically well-positioned for these roles.

What should I include in my resume when applying to Datadog?

Focus on demonstrating relevant technical skills, quantifiable achievements, and experience at scale. For engineering roles, highlight distributed systems experience, relevant programming languages, and cloud platform expertise. For sales roles, include quota attainment, deal sizes, and industry-specific experience. For all roles, use keywords from the job description, maintain a clean ATS-friendly format, and showcase your ability to operate in a fast-paced, data-driven environment.

How long does Datadog's interview process typically take?

While timelines can vary by role and team, many candidates report that Datadog's interview process typically spans 3-6 weeks from initial application to offer. This commonly includes a recruiter screen, one or more technical or functional assessments, and a final interview loop with multiple team members. The process tends to be thorough but well-organized, with recruiters generally keeping candidates informed of next steps and timelines.

Does Datadog offer remote work options?

Datadog's approach to remote work varies by role and team. Some positions are listed as remote-eligible, while others are tied to specific office locations such as New York, Paris, Dublin, Singapore, or Sydney. It's best to check the specific job listing for location requirements. The company has historically maintained a strong in-office culture, but like many tech companies, has adapted its policies over time. Review each posting carefully for the most current location and work arrangement details.

What is Datadog's company culture like?

Datadog is commonly described as having a fast-paced, technically rigorous, and collaborative culture. The company values ownership, intellectual curiosity, and data-driven decision-making. Engineers are often expected to have product sense, and go-to-market teams are expected to have strong technical acumen. The company ships products rapidly and encourages employees to take initiative. Many employees and candidates note a strong emphasis on continuous learning and a meritocratic environment where impact is recognized.

Should I write a cover letter when applying to Datadog?

While a cover letter may not always be required, including one can be beneficial — especially if the Greenhouse application form provides a field for it. A well-crafted cover letter allows you to explain your specific interest in Datadog, connect your experience to the role's requirements, and demonstrate knowledge of the company's products and mission. Keep it concise (250-400 words), specific to the role, and focused on what you can contribute rather than generic statements about wanting to work at the company.

Sample Open Positions

View 450 Open Positions at Datadog →

Related Resources

Similar Companies

Sources

Datadog Careers Page — Datadog
Datadog Company Overview — Datadog
Greenhouse Applicant Tracking System — Greenhouse Software
Datadog Investor Relations — Datadog
Datadog on Glassdoor - Interview Reviews — Glassdoor