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, 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 (pre and hopefully post-Covid) and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive. Visit us at Netskope Careers. Please follow us on LinkedIn and Twitter@Netskope.
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 Data Engineering team builds and optimizes systems spanning data ingestion, processing, storage optimization and more. We work closely with engineers and the product team to build highly scalable systems that tackle real-world data problems and provide our customers with accurate, real-time, fault tolerant solutions to their ever-growing data needs. We support various OLTP and analytics environments, including our Advanced Analytics and Digital Experience Management products.
We are looking for skilled engineers experienced with building and optimizing cloud-scale distributed systems to develop our next-generation ingestion, processing and storage solutions. You will work closely with other engineers and the product team to build highly scalable systems that tackle real-world data problems. Our customers depend on us to provide accurate, real-time and fault tolerant solutions to their ever growing data needs. This is a hands-on, impactful role that will help lead development, validation, publishing and maintenance of logical and physical data models that support various OLTP and analytics environments.
What's in it for you
- You will be part of a growing team of renowned industry experts in the exciting space of Data and Cloud Analytics
- Your contributions will have a major impact on our global customer-base and across the industry through our market-leading products
- You will solve complex, interesting challenges, and improve the depth and breadth of your technical and business skills.
What you will be doing
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Lead the design, development, and deployment of AI/ML models for threat detection, anomaly detection, and predictive analytics in cloud and network security.
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Architect and implement scalable data pipelines for processing large-scale datasets from logs, network traffic, and cloud environments.
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Apply MLOps best practices to deploy and monitor machine learning models in production.
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Collaborate with cloud architects and security analysts to develop cloud-native security solutions leveraging platforms like AWS, Azure, or GCP.
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Build and optimize Retrieval-Augmented Generation (RAG) systems by integrating large language models (LLMs) with vector databases for real-time, context-aware applications.
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Analyze network traffic, log data, and other telemetry to identify and mitigate cybersecurity threats.
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Ensure data quality, integrity, and compliance with GDPR, HIPAA, or SOC 2 standards.
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Drive innovation by integrating the latest AI/ML techniques into security products and services.
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Mentor junior engineers and provide technical leadership across projects.
Required skills and experience
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AI/ML Expertise
- Proficiency in advanced machine learning techniques, including neural networks (e.g., CNNs, Transformers) and anomaly detection.
- Experience with AI frameworks like TensorFlow, PyTorch, and Scikit-learn.
- Strong understanding of MLOps practices and tools (e.g., MLflow, Kubeflow).
- Experience building and deploying Retrieval-Augmented Generation (RAG) systems, including integration with LLMs and vector databases.
Data Engineering
- Expertise designing and optimizing ETL/ELT pipelines for large-scale data processing.
- Hands-on experience with big data technologies (e.g., Apache Spark, Kafka, Flink).
- Proficiency in working with relational and non-relational databases, including ClickHouse and BigQuery.
- Familiarity with vector databases such as Pinecone and PGVector and their application in RAG systems.
- Experience with cloud-native data tools like AWS Glue, BigQuery, or Snowflake.
Cloud and Security Knowledge
- Strong understanding of cloud platforms (AWS, Azure, GCP) and their services.
- Experience with network security concepts, extended detection and response, and threat modeling.
Software Engineering
- Proficiency in Python, Java, or Scala for data and ML solution development.
- Expertise in scalable system design and performance optimization for high-throughput applications.
Leadership and Collaboration
- Proven ability to lead cross-functional teams and mentor engineers.
- Strong communication skills to present complex technical concepts to stakeholders.
Education
- BSCS or equivalent required, MSCS or equivalent strongly preferred
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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.
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