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Please note that the job is only available from the locations outlined. We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. 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: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You

We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. 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: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You have worked extensively with multiple types of data stores. You have contribute

As a Staff Engineer on the Data Platform Experience team, you'll help shape how Datadog engineering teams build, operate, and evolve products on the Observability Data Platform. You'll lead the design and delivery of shared platform capabilities that reduce developer friction, improve operational visibility, and enable engineering teams to move faster with confidence. This role combines deep distributed systems expertise with technical leadership across multiple teams, influencing platform strategy while remaining hands-on in the code. You'll have the opportunity to solve company-wide challenges spanning cost intelligence, operational tooling, platform health, and developer experience. 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: Lead strategic engineering initiatives that improve how product teams build, operate, and evolve services on the Observability Data Platform. Design and build scalable platform capabilities for cost intelligence, including cloud cost allocation, trend analysis, and optimization recommendations. Develop operational intelligence and self-service tooling that helps engineering teams understand platform health, troubleshoot incidents, and improve operational efficiency. Drive reusable platform services and developer workflows that increase engineering autonomy while reducing operational complexity across multiple products. Provide technical leadership across teams by influencing architecture, mentoring engineers, and raising engineering standards through hands-on technical contributions. Participate in the team's on-call rotation and continuously improve platform reliability, observability, and operational excellence. Who You Are: You have experience designing and building large-scale SaaS or cloud platforms with deep expertise i

The Security Libraries team owns the customer-side integrations behind Datadog’s run-time security products — App & API Protection , Workload Protection , and Code Security — shipping and maintaining security capabilities across seven open-source language libraries ( .NET , Java , Go , Node.js , Python , Ruby , PHP ) and a set of HTTP proxy integrations (Envoy, NGINX, and HAProxy), running inside thousands of production clusters worldwide. Recent work spans exploit prevention (RASP), WAF detections, API Security, code security (IAST and SCA), and AI-assisted onboarding. As Engineering Manager, you’ll lead part of this polyglot team, setting the technical bar and team culture while driving the pace at which new detections and AI-assisted capabilities reach customers. This is a hands-on role: you’ll balance people leadership, product and roadmap ownership, and the operational health of code that runs in production at massive scale, with room to grow into more of Datadog’s security portfolio over time. 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: Lead, grow, and develop a team of roughly 4-8 library engineers — coaching, giving direct feedback, and empowering senior ICs as technical leaders Own team delivery and productivity: planning, milestones, reviews, and the on-call rotation Set product direction with Product Management and balance priorities across App & API Protection, Workload Protection, and Code Security Stay technically close to the work — apply strong technical judgment, contribute code where it matters most, and keep quality and architecture high Build strong relationships and drive alignment across the language teams and product, backend, and frontend partners Shape team identity and culture, and own accountability when problems oc

Husky is what we call the distributed, petabyte-scale columnar event store at the heart of our Event Platform, which powers dozens of Datadog’s most popular products – Logs, RUM, APM , Cloud Network Monitoring, Netflow, and many more. Husky was built from the ground up at Datadog to store and query massive volumes of event data at low cost, with data fully queryable within seconds of arrival. As an Engineering Manager on Husky, you will lead one of a few closely collaborating teams that work directly on Husky’s internals. We own the full lifecycle of events stored by our Event Platform – whether it’s managing the ingestion of over 100 million events per second exactly-once , optimizing the persistence layer with lightning-fast compaction , tweaking our columnar format, timely deletion across hundreds of thousands of customer tables, or building the metadata service that enables hundreds of thousands of queries per second – you will be responsible for the growth and success of a team constantly meeting new scalability requirements driven by Datadog’s growing customer base and suite of products. 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: Manage a team of software engineers ranging from new grads to senior engineers, focusing on career development, inclusivity, and high impact Be a technical leader of the team; while the role may not involve frequent hands on coding, you’ll be reviewing architecture decisions, RFCs, and pull requests and ensuring what the team ships is high quality Partner with product teams to evaluate use cases, ensure smooth implementation, and prioritize new platform capabilities. Share on-call responsibilities with the rest of the team and ensure a culture of operational exc

Datadog’s Partner Marketing Team is looking for a Senior Partner Marketing Manager to drive strategic marketing initiatives with our Cloud Service Providers and Channel Partners in EMEA. In this role, you will own and execute marketing programs designed to increase partner engagement, generate leads, and expand awareness of Datadog’s solutions within the cloud provider and channel ecosystem. This position offers a high-impact opportunity to collaborate with cross-functional teams and senior leadership while shaping Datadog’s presence with our ecosystem of partners. 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: Develop and execute regional partner marketing programs, including webinars, demand generation campaigns, enablement sessions, industry events, and social media initiatives to drive engagement. Set cross-team strategy and execute plans, working cross-functionally across product, demand gen, and partnerships teams — often in ambiguous, fast-changing environments. Drive coordinated field alignment, co-sell motions, and partner-led pipeline with AWS, Google Cloud and Microsoft Azure Understand and work within regions and stakeholders across the South EMEA region to build the partner ecosystem Track and analyze the effectiveness of partner marketing initiatives, reporting on key performance metrics through internal and external quarterly OKRs to ensure continuous optimization. Translate partnership data into clear ROI narratives for leadership and client/partner audiences.This includes presenting partnership marketing strategies and results to stakeholders while demonstrating clear ROI and strategic value Build and own our EMEA presence at global conferences like AWS Reinvent, DASH and Google Cloud Next Who You Are:

We are a team of engineers that translate our real-world experience to help our user communities solve problems. With a focus on AI-accelerated workflows and next-generation developer ecosystems, you will have the opportunity to meet fast-moving teams where they are, helping them lay strong engineering foundations and broadening your impact to the developer community at large. This is a unique opportunity to use both your engineering depth and authentic storytelling skills to shape how the next wave of builders approach software health, scalability, and observability. What You’ll Do: Help developers hone their craft in an AI-accelerated world by exploring how AI coding assistants and rapid-prototyping tools change software workflows, and guiding teams on how to balance rapid prototyping with established engineering practices around performance, code health, and system reliability. Build in public by creating authentic, peer-to-peer technical content, sharing your engineering insights directly where modern developers collaborate in person and online. Drive a constructive, bidirectional feedback loop between fast-moving developer communities and our internal teams, translating real-world developer experiences into actionable product insights to shape our roadmap while advocating for user needs from the inside. Design and ship high-quality open-source boilerplate templates, quickstarts, and tools that make integrating observability seamless across AI native workflows, next-gen platforms (Vercel, Supabase, etc.), and cloud providers (AWS, GCP, Azure). Who You Are: A builder with approximately 10+ years of software engineering experience, ideally having shipped applications from scratch or worked within an early-stage startup environment where you've worn multiple hats. An AI-fluent developer who natively leverages AI coding assistants and rapid-prototyping tools as a core part of your regular, day-to-day development workflow. Multi-stack familiar, comfortable writing an

Datadog's Application Performance Monitoring (APM) provides deep visibility into the health, performance, and lifecycle of modern distributed applications, tracing requests from end-user devices (web and mobile) through to backend services. Our goal is to help customers detect root causes faster, optimize application performance, and improve resource efficiency at scale. As the Engineering Manager for APM Serverless, you will help define and deliver the end-to-end serverless APM experience, from auto-instrumentation through troubleshooting, and ensure that OpenTelemetry and Datadog-native customers alike have a frictionless and performant journey. You will also lead efforts to expand coverage of cloud-managed services across providers, ensuring customers can seamlessly trace and monitor critical services in all major and emerging cloud environments. We’re looking for an experienced engineering leader who thrives at the intersection of infrastructure and developer experience. You should care about well-designed APIs, observability-first thinking, and building systems that empower other developers. This is a high-leverage role that will influence how developers across the industry understand and instrument their serverless workloads. 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: Lead a polyglot team of 8-9 engineers and partner closely with Product and Engineering teams across Datadog to deliver industry-leading serverless capabilities that power consistent, scalable, and intuitive instrumentation across languages. Drive a domain that is technically rich: Lambda, Azure Functions, GCP, OTel billing, Rust, durable functions, distributed tracing across managed services. Engineers on this team work

The data management software market is transforming how organisations build and run applications. MongoDB is the leading developer data platform and the first database provider to IPO in more than 20 years. Join us at the forefront of data and application development. MongoDB Technical Services Engineers combine deep technical expertise with exceptional problem-solving and customer-service skills. You’ll advise customers and resolve complex challenges across MongoDB Core, drivers, Atlas, Cloud Manager, cloud platforms, and infrastructure. We’re looking for candidates based in Dublin to join our vibrant office and collaborative in-office team. This is a five-day role with one of the following schedules: Tuesday–Saturday, Sunday–Thursday, or a five-day pattern covering both Saturday and Sunday. Under our hybrid model, employees on weekend schedules are expected to work from the office two days per week. Cool things you’ll do You’ll help customers troubleshoot complex issues and run critical MongoDB workloads with confidence. You’ll: Solve customer challenges across architecture, performance, recovery, and security Lead investigations from diagnosis to resolution, providing clear, actionable guidance Partner with Product Management and Engineering to advocate for customers and improve MongoDB Build tools, documentation, and training while mentoring peers and raising technical excellence What you need We value curiosity, adaptability, strong technical foundations, and a genuine desire to help customers. You should bring many of the following: 5–6 years of experience in technical support, systems engineering, database administration, SRE, or a related field Experience running complex, mission-critical production database systems Strong Linux and systems engineering skills, including performance, memory, I/O, storage, networking, security, clustering, and troubleshooting A solid understanding of networking concepts and protocols, including DNS, TCP/IP, and SSL/TLS Ability

About the team Our Technical Services (TS) team members use their exceptional problem solving and customer service skills in conjunction with their deep technical experience to advise customers and to solve their complex MongoDB problems. The Curriculum Engineer will work closely with this team and the rest of the TS Enablement program in order to create and maintain technical education modules for both new and upskilling team members to perform their support tasks at the highest levels. Responsibilities include designing,creating and delivering interactive internal training modules in cooperation with technical leaders and subject matter experts. We are looking to speak to candidates who are based in Vancouver for our hybrid working model. Responsibilities Develop, maintain, and continually improve internal training materials (videos, slides, reference materials, evaluations, etc.) Identify technical and procedural training needs across the team Help foster a culture of continual learning, skill sharing through live training, coaching and mentoring Build out the training curriculum, module hierarchy and training policies Foster subject-matter expert contributions to the creation and review of technical content Establish and report on training KPIs and success metrics Create environments and technical exercises for hands-on engineering workshops Improve practices and tooling related to the training content lifecycle Evaluate and recommend the most effective delivery methods for training Suggest the appropriate cadence to keep key skills fresh as well as supporting new product and feature readiness across the organization Work with a globally distributed team across multiple time zones Requirements Experience developing and delivering technical education/training Experience consolidating and presenting technical concepts from subject-matter experts Familiarity with course development methodologies Proven success in creating, delivering and man

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to achieve exceptional results for our customers. We are looking to speak to candidates who are based in Mexico City for our hybrid working model. Cool things you’ll do MongoDB is on a mission to change the way people think about databases. Along the way, our customers encounter questions and issues about how our approach to databases works for their use case. In Technical Services, it's our job to help these people. You'll be working alongside our largest customers, solving their complex issues - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on standard methodologies in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - working with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. In addition, you will also be responsible for mentoring and ramping new team members and taking initiatives in building knowledge of new product lines within the MongoDB ecosystem. What you need We consider all candidates with an eye for those who are self taught, insatiably curious, and multi-faceted. It’s important for candidates to check off these boxes: Systems engineering experience, including Linux

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. This is an opportunity to join a team that is responsible for all Observability systems that support metrics, metric visualization, logs, traces, and alerts for MongoDB. We are looking for engineers with high standards, and experience in setting direction and technical leadership for large engineering teams in designing and operating complex distributed systems, with strict SLO on security, durability, availability and performance. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Splunk, Flink, WarpStream/Kafka, Java, Golang Fluentbit. In addition to owning critical components of our observability infrastructure, as a Staff engineer on the team, you’ll also work closely with other SWE, Product and SRE teams to promote and implement best practices in instrumenting and monitoring their services. This is a highly collaborative role, and you will get to own some of the most relied upon internal infrastructure at Mongo. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a deeply technical leader on a collaborative team that applies low-level systems expertise to build the foundational infrastructure of a popular database, join us! Let’s build a faster, more reliable, and exceptionally observable database system together. W

MongoDB is building a world-class team in North America to create tooling that helps customers modernize their applications and migrate their data from legacy relational databases to MongoDB in real-time. As companies modernise legacy workloads and data ecosystems, they are increasingly drawn to the flexibility and scalability of the document model. The tools developed by the Code Generation and Data Migration team are critical in this journey, helping customers with schema modeling, code generation, initial data loads, and continuous data synchronization. We're looking for a Software Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges. This role will be based out of Washington, Oregon, or California. The ideal candidate for this role will have 2+ years of engineering experience in backend systems, distributed systems, or core platform development Experience in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory ma

MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhere—on premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. Atlas Search is a multi-cloud service that allows users to execute complex full text and vector search queries using the MongoDB Query Language . Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team builds and maintains the instances and supporting infrastructure powering Atlas Search. This platform deploys and monitors search deployments, providing a highly scalable yet observable system for customers and engineers. The Atlas Search product is quickly gaining traction with customers and we are shipping core infrastructure components that enable this growth. This role is based in San Francisco, CA with an in-office or hybrid work model. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software and automation in complex codebases Experience developing distributed systems and multithreaded applications Familiarity with public cloud platforms, distributed infrastructure, and metric-based development Experience with at least one modern statically typed program

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