The posting, in Datadog's own words
archived Oct 23, 2026The 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
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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.