const engineer = {
name: "Priyansh Salian",
titles: ["Software Engineer", "Data Engineer", "Analytics Engineer"],
experience: "5+ years in production systems & data platforms",
focus: [
"Distributed Systems & Event-Driven Architecture",
"Data Engineering — Pipelines, Warehouses, Streaming Analytics",
"AI Infrastructure & ML Platform Engineering",
"Cloud-Native & Kubernetes Platform Engineering",
"Full-Stack Product Engineering",
],
looking_for: [
"Senior Software Engineer",
"Data Engineer / Analytics Engineer",
"Staff Engineer",
"AI Infrastructure / Platform Engineering",
"Backend / Distributed Systems",
],
contact: "psalian1@hawk.illinoistech.edu",
site: "https://priyanshsalian.me",
};| 🖥️ Systems Deployed | 📡 Events / Day | 🗄️ Data Processed | ⏱️ Uptime SLA | 👷 Engineers Enabled |
|---|---|---|---|---|
| 40+ | 15 Billion | 2.4 Petabytes | 99.99% | 300+ |
Languages
Frontend
Backend & APIs
Infrastructure & Cloud
AI / ML
Building data infrastructure that turns raw event streams into business intelligence — from ingestion to insight.
Databases & Warehouses
Streaming & Pipelines
Analysis & Visualization
What I build with data:
📥 Ingestion → Kafka producers, CDC pipelines, REST/event connectors
🔄 Transformation → dbt models, Spark jobs, Flink streaming SQL
🏠 Storage → Lakehouse (Iceberg + S3), Snowflake DWH, ClickHouse OLAP
📈 Analytics → Sub-second dashboards, real-time metrics, anomaly detection
🤖 ML Pipelines → Feature engineering, model training pipelines, inference serving
| Project | Description | Scale |
|---|---|---|
| 🧠 NeuralMesh | Distributed ML inference orchestration — Kubernetes-native, multi-region | 2.3M req/min · 47ms p99 · 99.99% uptime |
| ⚡ StreamForge | Kafka-native event streaming backbone — schema registry, Flink processing | 15B events/day · 4.2M/s throughput · 0 message loss |
| 🚀 Nexus Deploy | Multi-cloud deployment orchestration — blue/green, canary, auto-rollback | 12K deploys/day · 45s MTTR · 300+ teams |
| 🔭 ObserveIQ | Full-stack observability — metrics, logs, traces, ML-powered alerting | 800K metrics/sec · −91% alert noise · <200ms queries |
| 📊 DataPulse | Streaming SQL analytics engine — Arrow-native, Iceberg cold storage | <800ms queries · 2.4PB data · <1s freshness |
| 🔍 VectorNova | High-performance vector database — custom HNSW, tiered storage | 100B+ vectors · <5ms search · 1M writes/s |
| 🛡️ SentinelAI | AI security intelligence — LSTM anomaly detection, LLM incident triage | MTTD: 4h → 3min · −94% false positives |
| 🌐 Prism Gateway | Enterprise LLM API gateway — semantic caching, PII redaction, 15+ providers | 78% cache hit rate · $2M/mo cost saved · <3ms overhead |
5+ years shipping production systems and data platforms at scale. If you're building something ambitious — let's talk.
