3 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Own the architecture and roadmap for Network Observability’s ingestion, processing, and storage layers.
- Build collection pipelines for SNMP, gNMI/streaming telemetry, syslog, flow data, network events, logs, and metrics.
- Implement real-time processing for normalization, enrichment, deduplication, and correlation, along with batch and backfill pipelines.
- Define schemas, serialization formats, data contracts, delivery semantics, replay behavior, and data quality checks.
- Select and design fit-for-purpose OLAP, time-series, and log/event storage while managing data modeling, retention, downsampling, cost, and performance.
- Translate ambiguous network health and anomaly-detection problems into use cases, phased delivery plans, MVPs, and success metrics.
- Partner with product, NOC, network engineering, API, and AI teams to deliver governed data surfaces for operators, customers, APIs, MCP servers, and AI agents.
- Define and monitor pipeline SLOs for freshness, completeness, and accuracy, and lead root-cause analysis for data gaps, lag, cardinality explosions, and schema drift.
- Write design documents, lead architecture reviews, contribute production code and on-call work, mentor engineers, and review designs and code.
- Use AI-assisted development tools and help establish practices for reviewing AI-generated code.
Requirements
- 7+ years of software engineering experience, including significant experience building large-scale data pipelines, streaming platforms, or telemetry systems.
- Deep hands-on experience with at least one major streaming platform such as Kafka, Pulsar, NATS, or RabbitMQ.
- Production experience with stream processing using Flink or a similar technology and batch processing using Spark.
- Strong understanding of network observability data and protocols, including events, logs, metrics, SNMP, gNMI, syslog, and flow data.
- Experience storing and querying telemetry at scale with ClickHouse, Druid, or similar OLAP systems and Prometheus/Thanos or similar time-series systems.
- Working experience with ELK/Elastic or OpenSearch.
- Strong programming skills in Java/Spring Boot or Python.
- Daily use of AI coding assistants and familiarity with MCP or structured tool interfaces for AI agents.
- Ability to break down ambiguous problems into incremental deliveries and lead features end to end.
- Strong written and verbal communication skills.
- Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
- Preferred experience in network EMS/NMS, telecom, data center, or interconnection environments such as Equinix Fabric.
- Preferred knowledge of BGP, OSPF, MPLS, CMDB, DCIM, and graph models.
- Preferred experience with OpenTelemetry, Grafana, Loki, Kubernetes-based data platforms, ML/AI data products, MCP servers, or open-source contributions in streaming, observability, or data infrastructure.
Tech Stack
Apache FlinkApache KafkaApache SparkClickHouseGrafanaJavaKubernetesPrometheusPythonRabbitMQSpring Boot
Categories
BackendData Engineering
About Equinix
Equinix is a public digital infrastructure company that operates a global platform of colocation and interconnection data centers for enterprises, cloud and network providers. It sells space, power, and connectivity, plus services such as Equinix Fabric, Network Edge, and Equinix Metal for hybrid multicloud and edge deployments. Founded in 1998 and headquartered in Redwood City, California, it is listed on NASDAQ (EQIX) and runs hundreds of IBX facilities across major metros worldwide.