Cost Estimation Manager Jobs

We are building the best platform in the world for engineers to understand, scale, and protect their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, application tracing, and security insights for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way . At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Solve a scaling bottleneck in a critical service Deploy a new feature to production, progressively rolling it out with feature flags Investigate and fix a production issue from a service your team owns Design a way to scale up a service for more traffic With your team, plan the most important projects to work on next Who You Are: You have significant experience in one or more languages You value code simplicity and performance You can design architecture to solve problems at high scale You have a BS/MS/PhD in a scientific field or equivalent experience You want to work in a fast, high-growth startup environment that respects its engineers and customers You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You have demonstrated ability to use AI coding tools in day-to-day workflows and build, validate, and refine AI-generated output in products You can design AI Backend systems, with awareness of quality, cost, and latency tradeoffs Bonus: You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products Datadog values people from all walks of life. We understand not everyone will meet all

At Datadog, we’re on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Observability Data Platform (ODP) is the backbone of everything Datadog delivers – powering how data is ingested, stored, routed, and surfaced across every product at planet scale. As a Senior Product Manager for ODP, you will work with world-class engineers and cross-functional partners to shape how the platform is deployed, controlled, and operated. You will define product direction across the control plane and data layer, translate complex infrastructure trade-offs into clear roadmap decisions, and help customers get the most from their observability investment – regardless of architecture, topology, or scale. 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 Will Do: Develop a deep understanding of the Observability Data Platform customers – platform engineers, SREs, and product managers that own the product verticals – their infrastructure challenges, deployment topologies, and cost-to-serve trade-offs. Define product direction across multiple ODP surfaces, including the control plane and data layer, by articulating clear problem statements and desired outcomes, and partnering with engineering on technical approach and sequencing Lead conversations with design partners and strategic customers to understand real-world platform pain points, validate product assumptions, and guide solutions from early prototypes through General Availability Develop a co

Applied AI is where Datadog's ambitious AI bets get built and shipped ( Bits Chat , updog ). We sit at the intersection of research and product: turning promising capabilities from Datadog AI Research lab and the research community into production systems that reach real customers. The team builds specialized models that replace frontier models where they are not necessary, making AI capabilities faster, cheaper, and more secure. The mandate is to move fast from idea to customer impact, and when a product finds its footing, to set it up for growth. As a Manager I in Applied AI, you will lead a team of engineers and applied scientists working on one of these challenges. You will define technical direction, run short feedback loops, make deliberate decisions about what to pursue or stop, and work closely with product managers, research teams, and cross-functional partners to ship AI capabilities that matter. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Lead and develop a team of engineers and applied scientists focused on cost-efficient specialized models and AI security capabilities Work closely with product managers, research teams, and cross-functional partners to shape the team's bets from initial framing through to broader adoption, with a clear definition of success criteria at each stage Own end-to-end delivery of high-quality AI systems, from early research exploration to production-grade reliability, with high standards for operational excellence, system reliability, and technical quality Navigate the unique challenges of shipping AI-powered products: balancing quality, latency, cost, and safety considerations. Drive evaluation and iteration practices for AI systems: define the quality bar and guide the team in building the offline

Datadog is seeking a Director of Product Management for Platforms to lead the internal platforms that power our global engineering organization. This is both a customer and internal platform leadership role, focused on enabling Datadog customers to maximize value with Datadog but also to enable other Datadog products to build, scale, and operate products efficiently and reliably. In this role, you will bring a combination of technical expertise, product management experience, and a deep understanding of platform and shared capabilities to help Datadog grow its leadership position. You will lead a team of product managers and collaborate with senior leadership in product, engineering and design. Your scope includes driving product features shared across all Datadog but also large-scale Datadog’s platform solutions. What You’ll Do Own the vision and strategy for platform products, ensuring alignment with overall company goals and customer needs. Identify new opportunities for innovation and drive them from concept to execution, ensuring they have a measurable impact on customers and the business. Define product roadmaps and manage the prioritization of features and initiatives to ensure the team's efforts are aligned with business goals. Drive Platform Adoption: Partner with engineering and product teams to ensure widespread adoption of shared platforms and shared features, reducing duplication and accelerating delivery. Improve Operational Efficiency: Improve developer velocity, time-to-production, and operational efficiency across Datadog’s engineering ecosystem. Collaborate with cross-functional teams including engineering, design, data science, marketing, and sales to deliver infrastructure product solutions that meet customer needs and business objectives. Define and Track Success Metrics: Define and track platform success metrics, including adoption of platform capabilities, reduction in internal toil, time-to-production improvements, cost efficienc

Datadog's Forward Deployed Engineering function is in an active growth phase, and the FDE Lead will play a central role in shaping what comes next. Working in close partnership with the Head of Datadog for Startups and Forward Deployed Engineers, and the existing FDE team, you will help define and expand the FDE framework, build out the structures and processes that allow the team to operate at scale, and extend the program's reach well beyond any single customer segment. This role sits at the rare intersection of sales, execution, program design, and hands-on engineering leadership. You are part field technical leader, part program architect, and part cross-functional connector. You will help determine what the FDE motion looks like at Datadog, contribute to its playbook, and push the boundaries of what the team can deliver. 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: Evolve and scale the FDE operating model end to end: engagement intake, scoping, sprint delivery, handoff back to account teams, and the success metrics (time-to-value, adoption lift, ARR influence, NPS) and reporting infrastructure that support them. Build out a catalog of FDE offerings spanning observability quickstarts, custom integration development, LLM/AI observability accelerators, CI/CD pipeline instrumentation, and cost optimization deep dives, and contribute to their pricing and business models, including free-to-paid conversion plays, paid deployment packages, and post-deployment success motions. Capture product and feature gaps uncovered during deployments, translate them into structured prioritized briefs, and partner with PM and Engineering to strengthen the field-feedback channel that informs roadmap decisions on a regular cadence. Hire, onboard, an

We’re looking for someone to join the Datadog Procurement team and help expand the Strategic Sourcing group. Make an impact by being a trusted analyst in several buying categories and continue to prove the value that Strategic Sourcing brings to the organization. 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: Leverage AI tools (e.g., Claude, ChatGPT) to enhance market research, accelerate data analysis, and improve efficiency in sourcing workflows Identify opportunities to incorporate automation and AI into procurement processes to drive scalability and smarter decision-making Support and execute sourcing strategies directed by sourcing managers with a specific focus in G&A categories (People Team, Finance, Legal, Real Estate) Develop strong relationships with stakeholders and assist teams to independently evaluate their best practices and adopt a value-driven mindset when purchasing on behalf of the organization Lead and execute Sourcing events (RFx) Negotiate pricing and other business terms with vendors on net-new purchases and renewals Manage the renewals list for designated categories and ensure accuracy of information and proactive communication Analyze spend data and identify potential cost savings opportunities Create pricing models based on vendor proposals to quantify various buying scenarios Build license forecast models and utilization analyses for enterprise software renewals to help uncover usage and savings opportunities Collaboratively align with adjacent functions like FP&A on utilization and forecast models Operate effectively in ambiguous or evolving problem spaces, helping bring structure, clarity, and forward momentum to loosely defined sourcing initiatives Monitor market trends that impact spend categories and

We are seeking a highly skilled Staff IT Product Manager for Internal AI to drive the strategy, delivery, and adoption of AI-powered solutions across our enterprise IT landscape. This role will be pivotal in shaping how AI transforms our internal operations, from service delivery and knowledge management to automation and decision support. The ideal candidate has a proven track record of managing enterprise-scale AI/ML products, collaborating across IT and business functions, and delivering measurable impact. We are looking to speak to candidates who are based in San Francisco, CA or Palo Alto, CA for our hybrid working model. Key Responsibilities AI Product Strategy & Roadmap Define and execute the internal AI product strategy aligned with enterprise IT and business goals Own multiple product lines in the internal AI product space Prioritize high-value use cases across IT functions (helpdesk, infrastructure, security, applications, enterprise data) Balance quick wins (AI copilots) with longer-term bold initiatives (AI-driven automation and decision-making) Experience in implementing AI solutions for enterprises our size and scale. This should include enabling agentic platforms for organizations and bringing to the table the best practices, pitfalls and learnings from such experiences Product Management Execution Embrace the product mindset and own the lifecycle of AI products—from ideation, critical user journey definition, requirements gathering, vendor evaluation, prototyping, and implementation to scaling in production Define and manage product backlogs, roadmaps, and success metrics Drive adoption and ensure AI solutions are delivering measurable outcomes (efficiency, cost savings, user experience) Stakeholder Engagement Partner with IT leaders (Applications, Infrastructure, Security, Service Desk) to identify pain points and AI opportunities Collaborate with business stakeholders to ensure alignment and secure sponsorship for AI initiatives Communica

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

We are looking for a detail-oriented and collaborative Finance Systems Administrator to join the Finance Systems team in India. This is a hands-on, service-delivery role responsible for day-to-day L1 support, user administration, and configuration changes across MongoDB's suite of Finance applications. You will be the first point of contact for end users encountering issues or making requests across NetSuite, Coupa, Concur, Graphite, YayPay, EPM system, and associated Tax & Treasury platforms. You will triage, resolve, or escalate tickets, maintain user access, support month-end activities, and help improve operational processes over time. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Key Responsibilities L1 Support & Ticket Management Own the L1 support queue for all Finance applications — triage, prioritise, resolve, or escalate tickets per defined SLAs Troubleshoot common functional issues: data entry errors, workflow approvals, report access, login/SSO problems, and configuration mismatches Document known issues and resolutions in a shared knowledge base; contribute to runbooks and FAQs to reduce recurring tickets Communicate timely and clearly with end users on ticket status, expected resolution, and workarounds User Administration & Access Management Provision, modify, and deprovision user accounts across NetSuite, Coupa, Concur, Graphite, YayPay, and Anaplan/Pigment - set up SCIM where applicable Assign roles, permission sets, and approval hierarchies in line with access control policies and least-privilege principles Run regular access certification reviews and clean up inactive accounts Coordinate with HR and IT during onboarding/offboarding events to ensure timely access changes Configuration & Admin Tasks Perform low-complexity system configuration: adding/updating cost centres, departments, approval workflows, expense categories, supplier records, and similar admin objects Support Finance te

About the Role We are seeking a Staff Enterprise Architect, Data to lead the strategy, design, and modernization of our enterprise data landscape. This role operates at the intersection of data architecture, engineering, and AI enablement, defining solutions to integrate our Data Lake and Data Warehouse across multi-cloud platforms. Over the next 12-18 months, you will enable self-service data access and natural language query capabilities for business users. You will architect Master Data Management and data lineage frameworks ensuring AI models operate on high-quality, governed data. You will also evaluate and implement AI-powered tools to automate data quality monitoring and enhance data security. We're looking to speak with candidates based in the San Francisco Bay Area for our hybrid working model. Key Responsibilities Data Strategy & Roadmap Design semantic layer architecture standardizing business metrics enterprise-wide. Define governance guardrails ensuring natural language queries access validated master data sources Develop Master Data strategy for Customer and Product domains (phases 1-2), Finance and People to follow. Define golden record requirements, stewardship models, and system-of-record hierarchy. Partner with business owners on master data governance Define cross-cloud data integration strategy and reference architecture. Specify patterns (federation, replication, abstraction layer) balancing performance, cost, and data freshness. Document trade-offs and recommend implementations for batch and near-real-time use cases Develop 12-24 month data architecture roadmaps for Finance, Sales, Product, and People. Identify capability gaps and recommend technology investments with business value and effort estimates Systems Design & Solution Leadership Evaluate AI-powered data observability platforms for quality monitoring, pipeline failure prediction, and data classification. Define requirements, lead vendor POCs, and establish integration patterns

The Site Reliability Engineering team designs and builds the global infrastructure on which we deploy our services, focusing on the above mentioned flagship MongoDB Atlas platform. As our customers grow and globalize, our services must satisfy demands for low-latency requests around the globe, and comply with various data sovereignty requirements. The SRE Team’s mission is to build this increasingly complex infrastructure, while continually lowering the operational burden associated with it, and increasing our internal visibility into the health of the system. We are strong believers in infrastructure-as-code and self-healing systems. The SRE Team is fully integrated with all the other engineering teams, and the teams work closely together with a soft and traversable boundary between their areas of responsibility. We are looking to speak to candidates who are based in New York City for our hybrid working model. Responsibilities Design and build the infrastructure for a global cloud service that comprises hundreds of thousands of MongoDB clusters, processes a billion metrics per day, and replicates tens of billions of database writes to our backup service Design, implement, and troubleshoot the automation and monitoring of services that seamlessly spans the globe - including several cloud providers Become an expert in infrastructure performance, helping us optimize from the application level all the way through the firmware Build for resilience. Our goal is that nobody’s pager goes off, ever. Are we there yet? No. Are we really close? Very. While we work on that - participate in a weekly on-call rotation Improve our infrastructure capabilities, optimizing for cost, simplicity, and maintainability Requirements 3+ years of experience running a mission critical service at scale in a Linux environment Firm grasp of at least one modern programming language, beyond basic scripting Familiarity with web and network protocols and standards (HTTP, TLS, DNS, etc) Bachelor’s deg

The Senior Global Payroll Transformation Manager is responsible for driving and supporting global payroll initiatives across compliance, equity, mobility, and payroll-related projects. This role focuses on enhancing payroll processes, ensuring global compliance, and delivering continuous process improvements that improve the employee experience. The successful candidate will identify root causes of operational challenges, collaborate cross-functionally to implement effective solutions, and evaluate systems, processes, and business requirements to optimize performance. They will also develop business cases, recommend strategic improvements, and lead the implementation of change initiatives across the global payroll function. This role can be based in Austin, TX, following a hybrid work model, or performed remotely from anywhere within the United States. Essential Job Functions and Accountabilities Represent Payroll as a key stakeholder in cross-functional initiatives impacting payroll operations Lead and manage global payroll projects and cross-functional initiatives in a fast-paced, time-sensitive environment Drive execution of payroll-related system implementations, enhancements, and third-party vendor integrations Partner with internal and external stakeholders to deliver projects on time, within scope, and aligned to business priorities Develop and present business cases outlining cost, risk, service, and operational impact to support decision-making Identify, prioritize, and implement process improvements to enhance scalability, efficiency, and accuracy of payroll operations Drive standardization of processes across regions, reducing reliance on manual interventions Lead efforts to improve the employee and stakeholder ex

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you’ll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource,