Level

Datadog

Manager I, Engineering - Cloud FinOps

Datadog is hiring a Manager I, Engineering - Cloud FinOps in New York, United States. It pays $192k-$240k a year and Level rates it ; you can apply on Datadog.

Level's read on this job

  • Level rates this role Uses AI ●●○○: an ordinary role that requires AI tools.
  • The posting allows some remote work.
  • Tools and skills the posting cites include Claude, Cursor and Claude Code.
  • Level classifies it as a lead role.
  • Level lists 433 other open roles at Datadog.

AI in this role

Lead an engineering team managing cloud finops and cost allocation data pipelines while utilizing AI coding assistants.

claudecursorclaude-code
engineering-managementcloud-finopsdata-pipelinescost-allocation

Datadog's Cloud FinOps team answers a question the business runs on: what does each product and each customer actually cost us to serve? Finance uses this team's output to close Datadog's books, Product uses it to compare cost to serve against what a customer pays, and engineering leaders use it to catch cost movements before they compound. As the Engineering Manager for this team, you'll own delivery across the runtime pipeline, coverage onboarding, and cost-to-customer identity mapping. You'll own the contracts that Finance and platform teams depend on. The core engineering problem is reproducibility: every dollar of cloud cost is placed against the product and customer that caused it, with lineage on every result and closed periods that replay exactly. This role starts by closing a coverage gap and grows into owning the model every platform team at Datadog onboards through.

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 and grow a team of engineers building the platform that allocates Datadog's cloud cost to products and customers, setting the operating rhythm across runtime and release, coverage onboarding, and identity and mapping.
  • Own the publication contract with Finance: versioned metrics with effective dates, backfill, and reproducible history, so any closed period can be replayed on demand and trusted for close.
  • Own the metric contracts with platform teams across Engineering, shifting cost facts to the teams that generate the cost so coverage growth stops scaling linearly with your headcount.
  • Partner with Revenue Engineering on the cost-to-revenue identity join that turns cost data into margin per product and per customer.
  • Drive continuous improvement in product and customer cost coverage and accuracy, and hold delivery commitments with teams that don't report to you.
  • Reduce key-person risk on runtime and compiler architecture by spreading ownership across the team, and use AI tooling (Claude Code, Cursor, and similar) to raise the team's speed and leverage.

Who You Are:

  • An engineering leader with experience managing data platform or data engineering teams building batch and pipeline systems judged on correctness and reproducibility.
  • You've shipped versioned publication with effective dates, backfill, and reproducible history.
  • You've held a delivery commitment with a team outside your reporting line, and you can describe what happened the first time a contract was missed.
  • You bring domain experience in metering, usage-based billing, cloud cost, revenue data, or financial data platforms.
  • You operate without a product manager in the loop on the external half of the job: you set the contracts, negotiate the boundaries, and drive the roadmap yourself.
  • If you've owned systems whose output is audited or closed by Finance (SOX scope, month-end close, revenue recognition), graph datasets or built retrieval-grounded systems where every answer cites its source and you know where a model shouldn't be trusted with a number at all, that is helpful experience.

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.

Benefits and Growth:

  • New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
  • Continuous professional development, product training, and career pathing
  • Intradepartmental mentor and buddy program for in-house networking
  • An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
  • Access to Inclusion Talks, our Internal panel discussions
  • Free, global mental health benefits for employees and dependents age 6+
  • Competitive global benefits

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. 

#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:$192,000—$240,000 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.

How we rate this

Manager I, Engineering - Cloud FinOps at Datadog rates 45 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.

Classification

Uses AI. An ordinary role that requires AI tools.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Engineering ManagementCloud FinopsData PipelinesCost AllocationClaudeCursorClaude Code

Questions you could be asked

  1. Tell me about a project where engineering management was part of your work. What did you do?
  2. Tell me about a project where cloud finops was part of your work. What did you do?
  3. Tell me about a project where data pipelines was part of your work. What did you do?
  4. Tell me about a project where cost allocation was part of your work. What did you do?
  5. Walk me through how you've used Claude in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Engineering Management, Cloud Finops, Data Pipelines, Cost Allocation, and Claude. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.

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