Sr. Manager, Quality Engineering
Netskope
| Company | Netskope |
| Category | Engineering |
| Location | Santa Clara |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 16 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
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 Netskope Careers. Please follow us on LinkedIn and Twitter @Netskope .
About the team
Our Data Engineering team is right at the heart of security, big data, and cloud computing. We process nearly 1PB of data every day with 99.99% uptime, delivering near real-time security insights to our customers. In this AI-driven world, data quality matters more than ever—which is why we’re looking for a seasoned manager to lead our Quality organization into its next phase.
Why you’ll love this role
You’ll lead the quality strategy for our core data infrastructure, working at a truly massive scale. We’ve moved away from the old "gatekeeper" model; instead, our quality engineers are embedded right in the development squads. They’re part of the team from day one, shifting testing left and sharing ownership of quality with developers. We measure success like engineers do: we look at deployment frequency, lead time, MTTR, and change failure rate—not just bug counts or pass rates.
You’ll also lead a high-leverage platform tooling team. You’ll be responsible for building the "paved roads"—the shared CI/CD gates, contract-testing infrastructure, and chaos templates—that allow teams across the org to move fast and independently, all while setting the technical standards and career paths for the whole organization.
What you’ll be doing
- Team Leadership: You'll lead and mentor 10+ engineers, fostering a culture of shared ownership.
- Strategy & Metrics: You’ll define our quality strategy and standards using DORA metrics (like deployment frequency and MTTR) rather than legacy QA metrics.
- Technical Guidance: You’ll guide teams in designing automation frameworks, contract-based testing, and resilience strategies for our complex systems.
- AI Integration: You'll oversee our rollout of AI-augmented testing—from LLM-driven test generation to evaluation frameworks for our AI products—making sure these tools actually accelerate our developers.
- Systems Integrity: You'll establish standards for data integrity and system reliability, even when things fail at scale.
- Cross-Functional Partnership: You’ll work closely with Engineering, Product, and Program Management to make sure quality is built into the architecture from the start.
- Operational Support: You’ll help with production deployments and lead root-cause analysis when things go wrong.
- Advocacy: You’ll build trust through influence, acting as a passionate champion for quality and customer success across the entire organization.
What you’ll bring
4+ years of management experience leading distributed teams of 10+ people.
A track record of building modern testing strategies and automation frameworks. Experience with contract/consumer-driven testing or chaos engineering is a big plus.
Deep experience with data systems like Postgres, Clickhouse, Trino, Spark, Iceberg, Kinesis, Kafka , and