Product Solutions Architect - FinOps

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. Datadog's Cloud Cost Management (CCM) suite helps Platform, Application Teams, Operations, FinOps, and Finance teams understand, allocate, and reduce cloud spend by putting cost data next to the observability data that explains it. As a Product Solutions Architect, you will partner closely with Datadog customers and the Cloud Cost Management product team to design product use cases, implement best practices, and drive adoption of CCM across customer environments. This includes infrastructure cost allocation, cloud costs, token usage, container costs, budgets, and optimization recommendations. 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. What You'll Do Serve as the in-house subject matter expert for Datadog's Cloud Cost Management products, including cost visibility across AWS, Azure, and GCP, Kubernetes and container cost allocation, custom and SaaS cost ingestion, budgets, anomaly detection, and cost optimization recommendations Provide architectural guidance on capacity planning, comparing cloud service cost models, and balancing performance vs. cost trade-offs across different cloud environments Guide customers on tokenomics and AI cost attribution across providers (Anthropic, OpenAI, AWS Bedrock, Google Gemini, Vertex AI, and GitHub Copilot), helping teams map API keys, models, and usage to teams and business units using Tag Pipelines. Help enterprise clients track real-time AI spend changes, set up cost anomaly monitoring, and connect token usage back to business outcomes and unit economics (such as cost per user or cost per ticket). Partner with Field teams to provide hands-on technical and architectural guidance to enterprise customers adopting CCM, including designing tagging and cost allocation strategies, showback and chargeback models, and cost reporting that connects spend to services, teams, and business units Create high-impact technical collateral, including reference architectures, technical guides, blog articles, and documentation to enable Field teams and the broader customer community, covering topics like cloud billing data onboarding (AWS, Azure, GCP billing), Kubernetes cost attribution, token usage, unit economics, and rightsizing and commitment optimization Act as a trusted advisor to Product Management by delivering actionable feedback informed by real-world field experience, helping shape the roadmap for cost allocation, multi-cloud cost visibility, token usage, optimization workflows, and FinOps integrations Who You Are You bring a strong engineering foundation, with hands-on experience managing, allocating, or optimizing cloud spend, or building FinOps programs and internal cost tooling in production environments at a large scale, and are comfortable diving deep into billing data and architectural tradeoffs to understand what drives cost You are familiar with cloud infrastructure and core observability concepts, such as tracing, metrics, and logging, and understand how compute, storage, networking, and container platforms (including Kubernetes) translate into cloud bills Deep understanding of cost models, performance characteristics, and capacity planning across various cloud services and managed platforms Experience with languages such as Python and/or SQL, and familiarity with querying and modeling large billing datasets, tagging strategies, and infrastructure-as-code 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 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 across engineering, FinOps, and finance stakeholders, including in high-stakes situations such as cost spikes, budget overruns, and commitment planning Demonstrates capability of utilizing AI tooling and scaling it  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 Solutions Architect, Sales Engineer, or FinOps practitioner supporting cloud cost management, FinOps, or cloud financial optimization tools (e.g., Cloudability, CloudHealth, Vantage, Kubecost, native AWS Cost Explorer, Azure Cost Management, or GCP Billing) Experience using Datadog and/or other observability tools in an SRE, DevOps, or platform engineering capacity, particularly owning cloud cost accountability or building internal cost reporting and automation Familiarity with FinOps Foundation practices, and with commitment management such as Savings Plans, Reserved Instances, and committed use discounts FinOps certification (e.g., FinOps Certified Practitioner) is a plus Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about technology and want to grow your skills, we encourage you to apply.