Skip to main content
← Back to Jobs

Manager I, Engineering - Core Analytics

DatadogNew York, New York, USA
Full-time
👁️ 7 views📝 0 applicationsPosted 4/29/2026Expires 10/5/2026
Tailor Resume for This JobCheck ATS Score

Get alerts for roles like this

More Manager I, Engineering - Core Analytics roles in New York, New York, USA — straight to your inbox. No account needed.

Applying to this role? Tailor your résumé to this job description in one click, then download it clean — no watermark, no subscription.

Job Description

You will lead a small, hands-on engineering team building the secure, scalable Core Analytics Data Access Platform that accelerates Datadog’s Applied AI and analytics capabilities. The team owns the Data Access Platform — a unified interface that lets AI and analytics teams discover and self-serve production-ready datasets while abstracting underlying systems and embedding required legal and compliance guardrails. In this role you’ll own technical direction, contribute to design and code, and partner closely with Applied AI, Product Analytics, and internal platform teams to provide reliable datasets and APIs for model training and analysis. This role balances day-to-day engineering leadership with long-term platform planning. 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 a Hands-On Engineering Team: Manage, mentor, and grow a small team of 2–4 data engineers (mix of senior and junior) across Paris and NYC, fostering technical excellence and career development. Own Technical Direction and Delivery: Define architecture, engineering priorities, and the team roadmap for the Data Access Platform, driving implementation of scalable, secure data pipelines and platform services. Contribute to Design and Code: Spend substantial time coding, reviewing, and shipping critical platform components to ensure performance, reliability, and operational excellence. Partner with Internal Stakeholders: Work closely with Applied AI, Internal Product Analytics, product managers, and platform teams to define data contracts, APIs, SLAs, observability, and curated analytical datasets. </

Required Skills

AWSETLLeadershipMachine LearningSparkTeam Building

The best-paying roles in your field. Every week. Free.

Join 10,000+ professionals getting job alerts and salary insights in their inbox

We respect your privacy. Unsubscribe anytime with one click.