Data Integration Engineer

Job Summary :

Key Responsibilities :

- Architect, develop, and support scalable ETL/ELT pipelines for ingesting data from network devices (routers, switches, firewalls) and platforms using SNMP, NetFlow/IPFIX, syslog, gNMI, sFlow, and APIs.

- Integrate telemetry and metrics from systems such as SONiC, Arista EOS, Cisco IOS/NX-OS, and various firewalls or controllers into centralized data lakes or observability systems.
- Build data connectors for both streaming and batch sources - covering technologies like Kafka, Splunk, Elastic, and time-series databases.

- Collaborate with network engineering and AI/ML teams to define effective data schemas and normalization approaches for topology, configuration, event, and performance information.

- Implement data quality validation, enrichment, and tagging to facilitate advanced correlation and root cause analysis.

- Work alongside DevOps and platform teams to deploy pipelines across Kubernetes environments and hybrid or on-prem clouds.

- Contribute to the design and documentation of data APIs, data contracts, and internal schemas to support both internal users and partners.

Required Qualifications :

- Minimum of 3 years experience in data engineering or integration, preferably in network-centric domains.

- Proven programming expertise in Python, Go, Rust, C++, or Java.

- Practical experience with network telemetry protocols (gNMI, SNMP, syslog, NetFlow, sFlow, OpenConfig) and API integration (REST, etc.).

- In-depth knowledge of data integration tools and cloud-native data services.

- Familiarity with message brokers (e.g., Kafka) and stream processing frameworks.

Preferred Qualifications :

- Working knowledge of data lakes and time-series databases.

- Background in AI/ML-driven networking solutions, such as network anomaly detection or

predictive analytics.

- Familiarity with open-source tools and projects such as Batfish, Prometheus, Grafana, or OpenTelemetry.