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Datadog

Large Enterprises

Most of these Datadog write-ups come from Software Engineers (23), then Machine Learning Engineers (5) and Frontend Engineers (1). The most reported rounds are the technical phone screen (20), the system design round (5), the behavioral / leadership round (2) and the hiring manager screen (1).

29 interview notes · updated Jul 2026

Datadog·Software Engineer·Technical Phone Screen

Jul 2026
Datadog SWE interview with a sliding window coding problem. Pretty focused on getting the implementation right under time pressure.
  • You have a list of datapoints, each with a set of tags, a timestamp, and a numeric value. Write a function that takes a tag t and a window size k, filters to only the datapoints containing tag t, and returns the sum for every consecutive window of k datapoints from that filtered set.

“Took me a minute to realize the windowing happens after filtering, not over the full dataset.”

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Datadog·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026
Behavioral round at Datadog for a software engineering role. One question the whole session, focused on communication and self-awareness. Pretty introspective stuff for an engineering interview.
  • Describe a time you got feedback that your communication was too long-winded. What was the situation, what exactly did someone tell you, and what did you actually do to fix it going forward?

“This one caught me flat-footed because I hadn't prepped a story specifically about communication feedback.”

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Datadog·Software Engineer·Technical Phone Screen

Jun 2026
Datadog software engineer interview with a data structures question that started simple but had a real follow-up with teeth. The trie optimization is where they actually wanted to see if you knew what you were doing.
  • Design a data structure that stores a set of prefix strings, then given a list of input strings, return every string that starts with at least one of those stored prefixes. No duplicates in the output even if multiple prefixes match the same string. Walk through a hash-based approach first, then optimize with a trie, and compare the complexity of both.

“I jumped straight to the trie because I thought that's what they wanted to see, and the interviewer pulled me back and asked me to do the naive version first.”

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Datadog·Software Engineer·Technical Phone Screen

Jun 2026
Security engineer interview at Datadog with a scenario-based question about social engineering and email compromise. Pretty open-ended, more of a think-out-loud exercise than a technical deep dive.
  • You're sitting across from the CEO of a well-known company at a coffee shop. How would you go about compromising their email account?

“This is less about knowing attack tooling and more about how you think through threat modeling from an attacker's perspective.”

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Datadog·Software Engineer·Technical Phone Screen

Jun 2026
Datadog software engineer interview with a coding problem focused on prefix matching. Started with a basic hashmap approach and then got pushed to implement a trie, which is where things got more interesting.
  • Design a data structure to store a set of prefixes. Given a list of input strings, output only those strings that match at least one stored prefix.

“Started with a hashmap and just checked every possible prefix length for each input string.”

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Datadog·Software Engineer·Hiring Manager Screen

Jun 2026
Short Datadog EM screen, basically just one question about where I'd spent my time as an engineer or manager. Not much to report.
  • What project have you spent the most time on?

“Seems straightforward but I fumbled it a bit.”

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Datadog·Software Engineer·Technical Phone Screen

Jun 2026
Datadog software engineering interview that revolved almost entirely around a single project deep dive. The structure was pretty demanding and I wasn't fully prepared for how much they'd push on the communication and stakeholder angle.
  • Walk me through one impactful project you've worked on, starting with a 60 to 90 second overview, then go deeper into the problem, your role, key decisions, and measurable impact.
  • What were the hardest trade-offs you faced during that project, and why did you make the calls you did?
  • How did you explain the technical complexity of this project to non-technical stakeholders, and what would you do differently looking back?
  • What was the single most difficult challenge you encountered, and how did you work through it?
  • What would you do differently on this project if you could go back, and what did you take away from it?

“I picked a project I thought was impressive but I spent way too long on the setup and barely got to the metrics before they nudged me forward.”

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Datadog·Software Engineer·Technical Phone Screen

Jun 2026
AI coding round at Datadog for a software engineer role. The main task was building a Snowflake query client and it went pretty smoothly, though the follow-ups pushed into less comfortable territory.
  • Implement a query client that connects to Snowflake, exposing a start_query method and a get_query_status method.
  • How would you handle secret management for database credentials in this kind of client?
  • How would you extend this client to support batch processing of multiple queries?

“Knocked this out pretty fast with AI assistance and it worked.”

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Datadog·Software Engineer·Technical Phone Screen

Jun 2026
Datadog software engineer interview with a deep project walkthrough. The whole thing was essentially one long question dressed up as a conversation, and they really do push into every corner of whatever project you bring up.
  • Walk me through a recent project in depth: what problem were you solving, what were the goals and constraints, what were your specific responsibilities and decisions, how was the system architected, what trade-offs did you make, what alternatives did you consider, what were the timelines and risks, how did you measure success, what were the actual results, and what would you do differently?

“This is one of those questions that sounds manageable until you realize they actually want all of it, not just the highlight reel.”

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Datadog·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Datadog for a software engineering role, basically a full YouTube design from scratch. Pretty broad scope and they pushed into a lot of subsystems, so it was a lot to cover in one session.
  • Design a video platform like YouTube, covering upload, transcoding, storage, streaming, and user-facing features like comments, likes, and recommendations.

“This one sprawls fast.”

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Datadog interview FAQ

What rounds are in the Datadog interview?

Candidates most often report a technical phone screen (20 write-ups), a system design round (5), a behavioral / leadership round (2) and a hiring manager screen (1).

What does the Datadog technical phone screen cover?

Across 20 technical phone screen write-ups, the most tagged question topics are Technical Trade-offs (30 questions), System Design (23) and Algorithms & Data Structures (17).