Sr. Software Engineer II (Distributed Systems)

📋 Description

• • Architect, build, and scale the distributed systems that power Narvar’s post-purchase platform, processing millions of events per day for 1,200+ global brands including Sephora, Levi’s, and Patagonia.
• • Own end-to-end design and delivery of high-throughput, low-latency microservices written in Java/Kotlin and deployed on Kubernetes across AWS and GCP, ensuring 99.99% uptime for critical customer touchpoints.
• • Lead cross-functional pods of 4-6 engineers to re-imagine how data flows between inventory, carrier, and consumer systems—turning billions of shipment updates into real-time, personalized experiences that drive 30% higher customer retention.
• • Drive the evolution of our event-driven architecture using Kafka, Pulsar, and DynamoDB streams, reducing average message processing time from 250 ms to <50 ms while cutting infrastructure costs by 18%.
• • Champion site-reliability best practices: establish SLIs/SLOs, automate chaos testing, and build self-healing mechanisms that detect and remediate anomalies before customers notice.
• • Mentor senior and mid-level engineers through rigorous design reviews, pair programming, and career-growth plans; your guidance directly impacts promotion decisions and shapes the next generation of technical leaders.
• • Collaborate with product managers and data scientists to translate complex carrier APIs and logistics data into elegant, scalable solutions—like predictive delivery-date models that improve accuracy by 22%.
• • Influence the technical roadmap by presenting architecture proposals to the CTO and VP Engineering; your decisions will determine how Narvar supports 10× traffic growth over the next three years.
• • Contribute to open-source projects (we maintain several Go and Rust libraries) and speak at meetups or conferences—Narvar covers travel and gives you 10% time for community work.
• • Debug gnarly distributed-tracing issues across 50+ services using OpenTelemetry, Jaeger, and custom tooling; turn root-cause analyses into actionable post-mortems that prevent recurrence.
• • Optimize data pipelines that ingest 5 TB of new data daily, leveraging Snowflake, Airflow, and dbt to deliver analytics-ready datasets in under 15 minutes.
• • Ensure security and compliance by design: implement OAuth2/OIDC, encrypt data in transit and at rest, and maintain SOC 2 Type II and ISO 27001 standards across all services.
• • Participate in a lightweight on-call rotation (one week every 6–8 weeks) with automated runbooks and generous comp-time policy—work-life balance is non-negotiable.
• • Experiment fearlessly: run A/B tests on new gRPC-based service meshes, evaluate Rust for performance-critical paths, and prototype with serverless edge runtimes to shave milliseconds off global API response times.
• • Celebrate wins together—whether shipping a zero-downtime migration of 200 million historical events or simply crushing a retro with homemade empanadas, the team ships and celebrates as one.