Product Solutions Architect - Product Analytics and Experimentation
Datadog · San Francisco, CA · 1 wk ago
HybridEngineeringFull-time
About the role
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.
Responsibilities
- Serve as an in-house subject matter expert for the 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 to the wider Datadog field technical teams over 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.
Qualifications
- 5+ years of experience solving complex problems for customers and a strong knowledge of building applications, specifically using product analytics, feature flagging, or digital experience tooling.
- You have 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, FullStory, PostHog).
- In-depth knowledge or experience with leveraging feature flag and experimentation tools (LaunchDarkly, Eppo, Split, Optimizely, etc.) and session replay platforms (FullStory, Contentsquare, Microsoft Clarity, etc.).
- Someone who can analyze Codebase and understands CI/CD, branch strategies and how that can influence Feature Flags.
- Experience with commonly used web and mobile languages and frameworks such as JavaScript, TypeScript, React, Python, iOS/Swift, Android/Kotlin, and file formats such as JSON and YAML.
- You are comfortable operating in rapidly evolving, ambiguous technical domains.
- You build deep context across teams and translate it into reusable, scalable solutions.
- You take ownership from problem definition through implementation and measurable outcomes.
- You are highly detail-oriented, particularly when working on architectures and customer-facing technical assets.
- You bring strong listening and consultative skills and are experienced supporting customers in high-pressure, complex situations.
- Able to sit up to 4 hours, traveling to and from client sites.
- Able to travel via auto, train, or air up to 40% of the time.
Bonus Points
- Successful track record with 5+ years experience working as a Growth Engineering
- Experience using Datadog and/or other observability tools with Product Analytics, or Feature Flags.
- Have proven experience deploying observability or analytics instrumentation in production environments at scale.
- Background in experimentation program design, defining success metrics, guard rails, and statistical significance frameworks for A/B tests.
- Experience with privacy-by-design and data governance for session replay, including PII masking, consent management, and data residency requirements in regulated industries.
- Experience collaborating with open source projects and active engagement within associated communities.