Manager I, Engineering - Cloud FinOps

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.