Senior Software Engineer, Streaming
Senior Software Engineer on the Streaming team responsible for architecting and evolving high-throughput, low-latency event streaming platforms that power real-time messaging and personalization at scale. Requires 5+ years building distributed streaming systems with deep expertise in Kafka/Flink and Java/Spring Boot.
About the job
What You’ll Accomplish
- Architect and evolve Attentive’s next-generation event streaming platform: Design high-throughput, low-latency solutions that power mission-critical messaging, personalization, and data integration use cases across Attentive’s ecosystem.
- Enhance self-service for product engineering and data teams: Build and refine self-serve tools for event observability, debugging, load testing, and system configuration, empowering teams to experiment and ship quickly.
- Simplify and modernize streaming architecture: Remove unnecessary abstraction layers, enable direct access for power users, and ensure the platform is flexible for both “paved path” and advanced use cases.
- Solve complex distributed systems challenges: Improve event delivery reliability, cost efficiency, and system integration for real-time and batch workloads.
- Champion best practices and technology selection: Stay ahead of industry advancements in event streaming, advocating for tools and approaches that balance innovation with long-term reliability.
- Collaborate across engineering: Partner with product, data, and infrastructure teams to launch new customer-facing features, integrations, and scalable solutions built on streaming infrastructure.
Your Expertise
- 5+ years experience architecting and supporting high-throughput, distributed systems at scale—especially those involving event streaming or messaging platforms.
- Deep understanding of the internals of distributed streaming frameworks such as Kafka, Flink, Pulsar, and/or Spark.
- Proficient in Java (Spring Boot) and familiar with modern development practices, including object-oriented design, data structures, and algorithms.
- Able to debug issues across the stack—from message serialization and event schemas to network and JVM tuning—and communicate tradeoffs clearly.
- Familiar with resource scheduling, data locality, and how infrastructure choices impact cost and system behavior.
- Experience with observability and developer tooling for streaming (e.g., tracing, metrics, replay).
- Infrastructure-as-code expertise (Terraform, Helm), comfortable with Kubernetes (EKS) and cloud-native environments.
- Track record of modernizing platforms: sunsetting legacy systems, moving to managed services, or implementing self-service capabilities.
- Excited by new technologies, but pragmatic about introducing them—focused on solving real business problems.
What We Use
- Infrastructure runs primarily in Kubernetes hosted in AWS’s EKS.
- Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm.
- Backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS.
- Automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas.
Compensation
The US base salary range for this full-time position is $150,000-$210,000 annually + equity + benefits.
Skills
Java, Spring Boot, Kafka, Flink, Pulsar, Spark, Kubernetes, EKS, Terraform, Helm, AWS, Distributed Systems, Observability
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