Principal Engineer, DEM

1 day ago


Bengaluru, India Netskope Full time

About Netskope Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security.  Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Paris, Melbourne, Taipei, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive.Visit us at Please follow us on and Twitter. About the role Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience. The (DEM Engineering team) is responsible for building data ingestions, analytics, API and AI/ML on timeseries network, user and application telemetry data generated from real user monitoring (RUM), synthetic monitoring, endpoint monitoring from Netskope SASE platform . We work closely with engineers and the product team to build solutions solving real world problems of Network Operators and IT Admins. What's in it for you As part of the Digital Experience Management team, you will work on state-of-the-art, cloud-scale distributed systems at the intersections of networking, cloud security and big data. You will be part of designing and building systems that provide critical infrastructure for global Fortune 100 companies. What you will be doing: 1. Architecting and Building Distributed Data Systems Design and implement large-scale distributed platforms, microservices, and frameworks. Build data ingestion pipelines that can handle millions of telemetry events daily, both streaming and batch. Ensure systems are fault-tolerant, highly available, and cost-efficient at scale. 2. Translating Complex Business Needs into Software Partner closely with the product team to understand complex operational and analytical requirements. Convert these into usable, performant, and maintainable technical solutions. 3. Technical Leadership Serve as a technical mentor and architectural guide for senior developers. Lead architecture reviews, design discussions, and code reviews. Influence engineering practices and promote best-in-class observability, reliability, and security. 4. Innovation in DEM and SASE Build solutions that enhance user experience monitoring — correlating data across network, endpoint, and cloud layers. Integrate AI/ML models for root cause analysis, anomaly detection, and forecasting on time series telemetry data. Continuously optimize data reliability, latency, and insight accuracy. Required skills and experience Core Technical Expertise 14+ years building scalable distributed systems in cloud-native environments. Expert-level ability to design and deliver complex technical solutions from architecture to production. Hands-on experience with data pipelines that handle massive throughput — both streaming (Kafka, Flink, Spark) and batch (ETL frameworks). Big Data Architecture expertise: data modeling, ingestion, transformation, and storage optimization (especially with systems like ClickHouse, Redis, Kafka). Programming and Systems Design Strong in Go, Python, or Rust — with advanced system design and algorithmic problem-solving. Deep understanding of networking and security protocols: TCP/IP, TLS, IPSec, GRE, PKI, DNS, BGP, routing. Strong grasp of web performance and telemetry concepts (latency, page load, route optimization). Cloud, Containerization, and SRE Proven experience designing/deploying on AWS or other cloud providers. Expertise in Docker and Kubernetes orchestration. Deep understanding of SRE principles — monitoring, alerting, SLIs/SLOs, and incident management. History of driving performance improvements, cost optimization, and reliability. Leadership and Communication Ability to mentor, influence, and set technical direction across teams. Excellent communication and documentation skills for diverse audiences. Proven track record of cross-functional collaboration with product, operations, and data science teams. Good to have Hands-on experience building APM, NPM, or DEM products. Prior work with AI/ML for time series analytics (root cause, anomaly detection, forecasting). Open source contributions related to big data, observability, or distributed systems. Advanced degree (MSCS or equivalent). What Makes This Role Unique This is not just another backend or data role — it’s at the intersection of cloud, network, and data intelligence.You’ll be shaping the core observability and performance layer for some of the world’s largest enterprise networks. It’s deeply technical, but also strategic and influential.It blends big data, cloud-native distributed systems, and AI/ML insights — all critical to Netskope’s SASE vision. Education BSCS or equivalent required, MSCS or equivalent strongly preferred #LI-SM1 Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment. Netskope does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate. Netskope respects your privacy and is committed to protecting the personal information you share with us, please refer to for more details.



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