Datadog for Startups - Forward Deployed Engineering Lead
New York, New York, USA; San Francisco, California, USANot specifiedLead
Salary not listed
AWSKubernetes
Is this role open to you?
New York, New York, USA; San Francisco, California, USA
Confirm work authorization, visa sponsorship and location requirements with the employer.
About the role
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.
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
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, and develop full-time FDEs, manage a rotating cohort of SWE and TSE secondments, build technical assessment frameworks suited to the customer-embedded nature of the role, and coach the team on engagement, scoping, stakeholder communication, and Datadog platform depth.
Identify high-value mini-product opportunities (integrations, dashboards, automation scripts, open-source tooling), drive lightweight engineering sprints that convert recurring customer needs into reusable assets, and maintain a prioritized build backlog informed by deployment learnings and competitive intelligence.
Help drive lightweight engineering sprints to convert recurring customer needs into reusable assets that scale across the FDE portfolio.
Partner with Sales, Solutions Engineering, Customer Success, and Business Development to identify which accounts enter the FDE motion, represent the function in QBRs and executive business reviews, and serve as a trusted advisor through complex deployment cycles.
Who You Are:
Have 8+ years of experience in forward deployed engineering, solutions architecture, software engineering, or related technical fields, including at least 3 years in a customer-facing technical role.
Have 2+ years of engineering management or technical leadership experience, including hiring, coaching, performance management, and cross-functional collaboration.
Have contributed to or scaled a technical program, practice, or new function within a high-growth technology company, with a track record of influencing product roadmaps through structured field feedback.
Bring deep familiarity with modern cloud-native stacks (Kubernetes, AWS/GCP/Azure, microservices, CI/CD pipelines, infrastructure-as-code) and hands-on experience with observability, monitoring, APM, or logging platforms; Datadog experience is a strong plus.
Communicate exceptionally across audiences from engineering leads and CTOs to VP-level executives, bring strong commercial instinct for how technical decisions translate to ARR, churn risk, and expansion, navigate large matrixed organizations without direct authority, and are comfortable with significant travel to embed with customers.
Entrepreneurial mindset, thrive in evolving environments, demonstrate strong business acumen, navigate matrixed organizations without direct authority, and are willing to travel to support customer engagements.
Datadog values people from all walks of life. We know 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 experience, we encourage you to apply.
Benefits and Growth:
Shape and scale a rapidly growing strategic function with significant influence on its operating model and future direction.
Partner directly with leadership across Engineering, Product, Sales, Customer Success, and Business Development.
Influence customer outcomes while helping inform Datadog's product roadmap through structured field feedback.
Work with a diverse portfolio of technically sophisticated organizations solving complex observability challenges.
Develop expertise across cloud infrastructure, platform engineering, AI observability, deployment strategy, and customer-facing technical leadership.
Gain visibility through participation in executive reviews, planning cycles, and cross-functional initiatives across the business.
Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.
Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.
To conform to US export control regulations, candidates should be eligible for any required authorizations from the US government. This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government.
#LI-Hybrid
Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.
The reasonably estimated yearly salary for this role at Datadog is: $200,000—$250,000 USD
----------------------------------------
About Datadog:
Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.
----------------------------------------
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.
Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.
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.
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
