About Aviz Networks Aviz Networks is an AI-driven networking company helping enterprises and service providers accelerate adoption of SONiC, open networking, and AI-powered operations. Backed by Cisco Investments and integrated with NVIDIA Spectrum-X, Aviz enables customers to standardize, simplify, and future-proof their network infrastructure.

Roles And Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines for ingesting data from network devices (e.g., routers, switches, firewalls) and platforms (e.g., SNMP, NetFlow/IPFIX, syslog, gNMI, sFlow, API)

Integrate telemetry and metrics data from systems like SONiC, Arista EOS, Cisco IOS/NX-OS, Firewall appliances and controllers into centralized data lakes or observability platforms.

Develop connectors for streaming and batch data sources, including Kafka, Splunk Elastic, and time-series databases.

Work closely with network engineering and AI/ML teams to define data schemas and normalization strategies for topology, configuration, event, and performance data.

Implement data quality checks, enrichment processes, and tagging to support correlation and root cause analysis workflows.

Collaborate with DevOps and platform teams to deploy data pipelines in Kubernetes-based environments or on-prem/hybrid clouds.

Contribute to the development of data APIs, data contracts, and documentation for internal consumers and partners.

Required Qualifications Bachelor’s or Master’s degree in Computer Science, Networking, Electrical Engineering, or related field.

3+ years of experience in data engineering or integration roles, ideally in network-centric environments.

Strong programming skills in Python, Go, Rust, C++ or Java.

Experience working with network telemetry protocols (gNMI, SNMP, syslog, NetFlow, sFlow, OpenConfig) and APIs (REST etc).

Proficiency with data integration tools and cloud-native data services.

Familiarity with message brokers (Kafka), and stream processing frameworks

Preferred Qualifications Experience integrating data from network observability platforms like NetQ, Cisco Nexus Dashboard, Arista CloudVision and streaming telemetry, API frameworks.

Knowledge of data lake and time-series databases.

Exposure to AI/ML workflows in the context of networking, such as anomaly detection or predictive analytics.

Familiarity with open-source projects like Batfish, Prometheus, Grafana, or OpenTelemetry.