Netskope: Sr. Staff Engineer, Data Engineering — Taipei, Taiwan

About Netskope

Netskope develops security and networking technology for cloud, data and AI environments. Its employer introduction identifies the Netskope One platform, a zero-trust engine and the NewEdge network as parts of that offering. The business describes giving organisations visibility and control while maintaining the performance of access to applications and information. This connects cybersecurity with networking: the products address both how digital resources are reached and how their use is controlled and protected.

The position and its setting

Netskope lists Sr. Staff Engineer, Data Engineering in Taipei, Taiwan, under reference 8184639. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Department: Data Engineering
• Employer listing date: 7 September 2026

Responsibilities and work described

• Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience
• We are seeking skilled engineers to build scalable distributed systems and integrate agentic AI and conversational analytics
• As a Senior Staff Engineer, you will lead the architecture, data modeling, and core infrastructure powering our next-generation AI and analytics platforms
• Architect, develop, and deploy global-scale distributed platforms and pipelines for massive data ingestion, transformation, and analytical reporting
• Design: and refine backend infrastructure supporting Agentic AI workflows, autonomous systems, and conversational analytics with natural language interfaces
• Partner with application teams to define data strategies and durable conceptual models spanning OLTP/OLAP and generative AI architectures (e.g., RAG)
• Evaluate data integration challenges and deliver optimized architectural solutions for complex business requirements
• Research emerging AI techniques and advanced machine learning methodologies to continuously enhance data design patterns
• Delivery: technical leadership and mentorship across the project lifecycle, focusing on efficient data modeling, prompt engineering, and high-performance data access services

Essential requirements and candidate background

• At least 8 years of hands-on experience in architecture, design, or development of enterprise data solutions, applications, and integrations
• Experience designing and deploying Agentic AI systems and working with AI application frameworks
• Communication, presentation, and interpersonal skills with the ability to articulate complex concepts clearly
• Bachelor or Master degree in STEM majors
• Proficiency: SQL, alongside familiarity with semantic search and Natural Language to SQL paradigms
• Experience building products using at least 1 of each of the following distributed technologies:
• Relational Stores (i.e. Postgres, MySQL, or Oracle)
• Columnar, NoSQL, or Vector Stores (i.e. Starrocks, Clickhouse, BigQuery, Pinecone or pgvector)
• Distributed Processing Engines (i.e. Apache Spark, Apache Flink)
• Distributed Queues (i.e. Apache Kafka, AWS Kinesis, or GCP PubSub)
• Experience: software engineering standard methodologies (e.g., unit testing, code reviews, design documents)
• Experience working with GCP, Azure, AWS, or similar cloud platform technologies
• #LI-SC3
• Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment
• 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

Preferred experience and additional strengths

• Algorithms, data structures, and coding background with either Java, Python, or Scala programming experience (Python highly preferred for AI/ML ecosystem compatibility)

Location, schedule and contract conditions

For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.

• Advertised location: Taipei, Taiwan

Conditions requiring the complete notice

Some passages contain complex or combined conditions that have not been reduced to short eligibility statements here. Read the complete linked notice for those passages, including any alternatives, exceptions or restrictions. The concise facts above should not be treated as the full wording of every condition.

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Sr. Staff Engineer, Data Engineering vacancy is not an offer for reference 8184639; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Netskope

Applications follow the official employer page linked below.

Open the official Netskope posting below and match the title and reference 8184639.

Compare your qualifications and experience with the essential conditions for the Taipei, Taiwan position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• Java
• SQL
• NoSQL
• Spark
• Kafka
• AWS
• GCP
• Azure
• AI/ML
• Google Cloud
• machine learning
• AI