- Location
- Taipei, Taiwan
- Level
- Staff
- Posted
- 23 October
About this role
Join the Future of Security at Netskope
Netskope (NASDAQ: NTSK) is a leader in modern security and networking for the cloud and AI era. We secure and accelerate cloud, data, and AI in real time, everywhere. Thousands of customers, including more than 30 of the Fortune 100, trust the Netskope One platform, its Zero Trust Engine, and the powerful NewEdge network to gain full visibility and control without performance trade-offs.
At Netskope, our technology is driven by our greatest strength: our people. We believe that belonging powers innovation, and success is both personal and organizational. We embrace differences in gender, ethnicity, beliefs, ability, and identity, creating an environment where every voice is heard and respected. We empower our employees to bring their authentic selves to work, grow their careers through continuous education and mentorship, and lead with transparency and curiosity. Join a team where you belong, where you are encouraged to be an entrepreneur, and where together, we continue to redefine the landscape of security.
Visit Careers at Netskope to learn more. Follow us on LinkedIn and Instagram.
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.
Netskope's Data Platform is the backbone behind every security insight our customers see, ingesting and processing security telemetry from a global edge network at massive scale. We own the full data path - from collection at the edge, through stream processing and enrichment, to the query, routing, and delivery systems that put that data in customers' hands. On top of that foundation we build the analytics, reporting, and export capabilities that our customers rely on to understand and act on their security posture. We are now investing in an AI-native future, building a semantic layer that makes our data machine-interpretable and agentic experiences that let customers ask questions of their data in natural language.
What you’ll work on
- Partner with architects to design and evolve the systems that carry telemetry from global edge ingestion through processing, query, and customer delivery, with a focus on scale, durability & latency.
- Raise the bar on observability, SLOs, deployment safety, and production resilience of the platform that others build on top of - not just a single service.
- Build the AI-native semantic layer that’s the foundation to make our data machine-interpretable, and the agentic experiences on top of it that let customers ask questions in natural language.
- Lead cross-team initiatives, shaping architecture through design reviews, and mentoring engineers, with the freedom to adopt modern & open source technologies.
Required skills and experience
- 10+ years building and operating large-scale distributed systems, with significant time operating at Staff-level (or equivalent) technical scope.
- Strong coding ability in one or more of Go, Java, Python, or C++, with a track record of shipping production systems, not just designing them.
- Experience designing for reliability at scale - observability, SLOs, incident response, and safe deployment on cloud infrastructure (AWS/GCP, Kubernetes).
- Demonstrated cross-team technical leadership: influencing architecture decisions, driving design decisions, and aligning teams around a direction.
- Experience building high-throughput ingestion and data services over modern RPC and wire protocols - HTTP/2, gRPC, and Protocol Buffers - including schema design and evolution.
- Experience with high-throughput data pipelines - data streaming & batch ingestion, processing, and storage using columnar data formats such as Parquet
- Excellent written and verbal communication, and the flexibility to collaborate across time zones with globally distributed teams.
- Ability to ramp up quickly into unfamiliar codebases and domains as priorities evolve, mentoring engineers and raising the engineering bar around you.
- Familiarity with, or strong interest in, LLM-based systems, semantic layers, or data modeling for AI applications.
Education
- BSCS or equivalent required, MSCS or equivalent strongly preferred
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 Netskope's Privacy Policy for more details.
The application window for this position is expected to close within 50 days. You may apply by filling out the below information, or visiting our Netskope Careers site.
As published by Netskope. Applications are handled on their site.
One click, then it is written
Apply to Netskope with a resume written for this role.
Queue Staff / Sr. Staff Engineer, Data Engineering and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Netskope’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
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Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
500 free credits on sign-up. No card. Nothing is sent until you say so.
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