Product Solutions Architect - Product Analytics and Experimentation

Product Solutions Architecture (PSA) Team

The Product Solutions Architecture (PSA) team acts as a technical multiplier across Datadog. PSAs are domain experts who partner with Field teams on complex customer use cases across pre- and post-sales engagements and scale their impact by producing reusable collateral, including reference architectures, technical guides, and enablement assets. By feeding real-world customer insights back to Datadog Product teams, PSAs help influence product roadmaps while accelerating adoption, usage, and long-term customer success.

The Digital Experience & Experimentation family of products includes Product Analytics, Feature Flags, Experimentation, and Session Replay and is a fast‑growing segment at Datadog that addresses product managers, digital experience teams, and product engineers building and optimizing customer‑facing applications.

As a Product Solutions Architect, you will partner closely with Datadog customers and the Product team to design architectures, implement best practices, and drive adoption of this digital experience product family across customer environments.

At Datadog, we place value in our office culture – the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work‑life harmony that best fits them.

• Serve as an in‑house subject‑matter expert for Datadog Product Analytics, Feature Flags, Experimentation, and Session Replay and related products.
• Partner with field teams to offer guidance on architecture choices, SDK instrumentation, data collection, and best practices to large Enterprise customers as they adopt the product family.
• Act as a trusted advisor to Product Management by delivering actionable feedback informed by real‑world field experience.
• Create high‑impact technical collateral, including reference architectures, technical guides, cookbooks, and documentation to enable Field teams and the broader customer community.
• Build world‑class training material, solutions briefs, blogs, and documentation for the wider Datadog field technical teams on the latest product features and capabilities.
• Collaborate with other teams at Datadog, including Marketing, Sales, Community, Documentation, and Evangelism, to ensure the success of the Product Analytics product family.
• Build proofs of concept and small‑scale deployments to validate solutions and reproduce real‑world customer environments.
• Collaborate on defining the technical GTM motion for Feature Flags and Experimentation, including competitive positioning against competitors, to enable Sales Engineers globally to run these conversations independently.

• 5+ years of experience solving complex problems for customers and strong knowledge of building applications, specifically using product analytics, feature flagging, or digital experience tooling.
• Excellent verbal and written communication skills.
• Familiarity with product analytics platforms and optimizing them for Enterprise‑level production usage (e.g., Adobe Analytics, Google Analytics, Amplitude, Mixpanel, Heap, Contentsquare, Full Story, Post Hog).
• Fluent in the digital experience and product analytics market domain, competition, technological shifts, and customer needs related to feature flag management, experimentation, and session replay.
• In‑depth knowledge or experience with leveraging feature flag and experimentation tools (Launch Darkly, Eppo, Split, Optimizely, etc.) and session replay platforms (Full Story, Contentsquare, Microsoft Clarity, etc.).
• Someone who can analyze codebase and understands CI/CD, branch strategies and how those can influence Feature Flags.
• Experience with commonly used web and mobile languages and frameworks such as JavaScript, Type Script, React, Python, iOS/Swift, Android/Kotlin, and file formats such as JSON and YAML.
• Comfortable operating in rapidly evolving, ambiguous technical domains.
• Ability to build deep context across teams and translate it into reusable, scalable solutions.
• Ownership from problem definition through implementation and measurable outcomes.
• Highly detail‑oriented, especially…