Level

Datadog

Senior Software Engineer - Analytics Data Platform

Datadog is hiring a Senior Software Engineer - Analytics Data Platform in Paris, France. Level rates it ; you can apply on Datadog.

Level's read on this job

  • On Level's scale, this software engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting allows some remote work.
  • Tools and skills the posting cites include Spark, PySpark and Ray.
  • Level lists 439 other open roles at Datadog.
  • The role was posted in the last few days.

AI in this role

Senior Software Engineer building batch data processing infrastructure and AI-driven version migration automation tooling.

sparkpysparkraypythongojavarustscalakubernetes
llm-integrationdistributed-systemsplatform-engineeringbackendai-assisted-automation

The Analytics Data Platform Batch team owns the platform that powers batch data processing across Datadog’s internal data infrastructure. We execute 800k+ Spark jobs daily - plus PySpark, Ray, and Python-based workloads - serving 50+ internal teams across billing, cost management, security intelligence, applied AI and more.

We are a platform engineering team: our customers are Datadog’s internal data engineers and scientists, and our product is the infrastructure, abstractions, and tooling they build on top of. We operate at the intersection of distributed systems, developer experience, cost engineering, and AI-assisted automation - working on problems that affect pipelines at scale

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:

  • AI-driven version migration automation: Spark and JVM
  • Building agentic tooling that analyzes compatibility, generates PRs, and orchestrates multi-datacenter testing
  • Engine-agnostic batch execution
  • Platform reliability and scale
  • Spark Pod Autosizing - CPU and memory allocations
  • Understanding tradeoffs across execution models

Who You Are:

  • You have 6+ years of experience
  • You have significant backend programming experience in one or more languages (Go, Java, Rust, Python, Scala)
  • Spark internals/infrastructure - executor lifecycle, memory model, dynamic allocation, resource tuning
  • Experience building platform or infrastructure that other engineers depend on
  • Distributed systems engineer with experience building high performance large scale systems
  • Kubernetes fundamentals
  • Excellent communication skills (English)
  • High proactivity and cross-team collaboration experience
  • You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how
  • You have demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output
  • Bonus: AI/LLM integration in engineering workflows & Observability and cost attribution

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

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

Senior Software Engineer - Analytics Data Platform at Datadog rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  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

LLM IntegrationDistributed SystemsPlatform EngineeringBackendAI Assisted AutomationSparkPySparkRay

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$168k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. How have you integrated a large language model into a production application?
  2. Tell me about a project where distributed systems was part of your work. What did you do?
  3. Tell me about a project where platform engineering was part of your work. What did you do?
  4. Tell me about a project where backend was part of your work. What did you do?
  5. Tell me about a project where ai assisted automation was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: LLM Integration, Distributed Systems, Platform Engineering, Backend, and AI Assisted Automation. 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.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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