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Job description
Today, everyone from PMs to Sales to SREs uses AI to query their business data - but every answer is a one-off with no governance, no consistency, and no visibility for data teams. We're building the system that fixes this: a context layer that learns from existing data tools driving high quality and consistent answers, an AI-powered query experience, full governance for data teams, and rich analysis surfaces to present and share the results. You'd be building a zero to one product of what we believe will become a major new product line for Datadog.
What You'll Do
Drive the product vision and roadmap spanning the Data agent experience, the semantic/context layer, governance console, chat experience and analysis surfaces (dashboards, notebooks, sheets)
Own the end-to-end product lifecycle from discovery to launch, working with a cross-functional team of engineers, designers and other PMs
Deeply understand the needs of two key personas: data teams (who govern and curate) and data consumers (PMs, engineers, SREs, executives who ask questions)
Design the context and governance layer that makes AI-powered analytics trustworthy - including auto-generation from existing BI tools, eval frameworks, confidence scoring, and self-improvement loops
Define how observability data and business data come together to serve unique use cases
Engage directly with early customers and internal dogfooding users to iterate on accuracy, usability, and trust
Independently research the competitive landscape across legacy BI vendors, warehouse-native analytics, AI-first startups, and AI labs
Work on the product pricing
Work with GTM teams to define positioning, packaging, and the path to displacing entrenched tools
Who You Are
5+ years of experience in B2B SaaS Product Management, with at least some of it spent on data-intensive or analytics products
You have domain knowledge of business intelligence, data visualization, semantic layers, data warehouses and the modern data stack.
Strong analytical skills - you can write SQL, interpret complex data, and use data to drive product decisions
Experience with AI/LLM-powered products is a strong plus - you understand prompt engineering, evals, and the unique UX challenges of non-deterministic systems
You are AI-pilled. You live in Claude Code or Cursor, have built unique AI workflows for yourself, hack around with new tools. etc
You have a strong sense of ownership with an entrepreneurial mindset - this is a 0-to-1 product that requires someone comfortable with ambiguity and speed
Sharp communication skills with the ability to interact with technical stakeholders and executives alike.
Bachelor's Degree in Engineering, Computer Science, Data Science, or equivalent experience is a plus
Benefits and Growth
Generous and competitive benefits package
New hire stock equity (RSUs) and employee stock purchase plan
Continuous career development and pathing opportunities
Employee-focused best in class onboarding
Internal mentor and cross-departmental buddy program
Friendly and inclusive workplace culture
Datadog offers a competitive salary and equity package, and may include variable compensation. The reasonably estimated yearly salary for this role is: $187,000—$253,000 USD.
Equal Opportunity at Datadog
Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.
Privacy and AI Guidelines
Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.
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Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.