2 days ago
Paris, FranceSenior
Responsibilities
- Build AI-driven automation for Spark and JVM version migrations.
- Develop agentic tooling that analyzes compatibility, generates pull requests, and orchestrates multi-datacenter testing.
- Build engine-agnostic batch execution capabilities and platform infrastructure at scale.
- Improve platform reliability and scale, including Spark pod CPU and memory autosizing.
- Evaluate tradeoffs across batch execution models and support internal data engineers and scientists.
Requirements
- 6+ years of experience.
- Significant backend programming experience in one or more of Go, Java, Rust, Python, or Scala.
- Experience with Spark internals and infrastructure, including executor lifecycle, memory models, dynamic allocation, and resource tuning.
- Experience building platforms or infrastructure used by other engineers.
- Distributed systems experience building high-performance, large-scale systems.
- Kubernetes fundamentals.
- Excellent English communication skills and experience with proactive cross-team collaboration.
- Demonstrated ability to use AI coding tools in daily workflows and validate, critique, and refine their output.
- AI/LLM integration in engineering workflows and observability or cost attribution experience are bonuses.
Benefits
- Hybrid workplace with an office culture focused on collaboration and work-life harmony.
- New-hire stock equity through RSUs and an employee stock purchase plan.
- Continuous professional development, product training, and career pathing.
- Intradepartmental mentor and buddy program.
- Inclusive company culture, Community Guilds, and access to Inclusion Talks.
- Global mental health benefits for employees and dependents age 6+.
- Competitive global benefits, which may vary by country and employment arrangement.
Tech Stack
About Datadog
Datadog builds a SaaS observability and security platform that monitors infrastructure, applications, logs, and services for engineering and DevOps teams. Its products include infrastructure monitoring, APM, log management, real user monitoring, and cloud security, sold via subscriptions and used across cloud-native and hybrid environments. Founded in 2010 and headquartered in New York City, Datadog is a public company trading on NASDAQ under the ticker DDOG.