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Staff Data Privacy Engineer Jobs

3,414 active opportunities Β· Updated for October 2026

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Explore current staff data privacy engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

I
Instacart
πŸ“ United Statesβ€’ Full-timeβ€’ Remoteβ€’ From $227K/yr
1mo ago

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best workβ€”whether it’s from home, an office, or your favorite coffee shopβ€”while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. OVERVIEW Every year, people across the world spend nearly one trillion dollars on groceries. But food is more than sustenance β€” it's identity, ritual, culture, and care. The way we eat shapes our health, our routines, and our relationships. Yet for most people, translating a desire to eat better or live healthier into actual, lasting habit change remains hard. The Instacart Consumer team is at the forefront of reimagining how people relate to food at home. We're building new product experiences around meals, nutrition, and health that go beyond the transaction β€” helping people discover what to cook, build routines that stick, and feel confident in the choices they make for themselves and their families. As a Staff Researcher on the Consumer team, you will shape the foundational understanding of how and why people change (or struggle to change) their food behaviors.

REMOTEawsrestai
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S
Snowflake
πŸ“ Menlo Parkβ€’ Full-time
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset β€” who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Staff Network Engineer Location: MPK/Bellevue/Dublin Snowflake's Enterprise Technology Network Services team is looking for a Senior Network Engineer to lead the design, operation, and optimization of our Zero Trust and secure-access platform. This role is Zscaler-centric β€” you will own the health, performance, and roadmap of our ZIA/ZPA deployment β€” while working across a modern, multi-cloud network stack that supports a global workforce of 10,000+ users. You'll be the escalation point for the most complex connectivity issues and a driver of automation and observability across the environment. What You'll Do Own and operate the Zscaler platform (ZIA, ZPA, ZDX, ZCC) end-to-end, including policy frameworks, app-segmentation models, PAC/traffic-forwarding standards, App Connector topology, and NSS/log-streaming design. Troubleshoot secure-access incidents like tunnel flapping, broker/connector health, SSL inspection edge cases, DNS/DTLS failures, and lead root-cause analysis for systemic issues. Manage Palo Alto firewalls, Panorama and GlobalProtect VPN, while planning migration toward Zscaler solutions. Support Aruba (Central) Wireless, Ekahau and Cisco Catalyst switches globally. Design, install, and configure network devices and ISP circuits at new offices. Build automatio

pythonvuesql
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Biohub
πŸ“ Redwood Cityβ€’ Full-timeβ€’ Hybridβ€’ $241K – $331K/yr
1mo ago

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The AI Cluster Production Engineering team is part of the AI Compute Platform organization at Biohub, a non-profit research lab committed to open science and open-source AI. We own the design, operation, and reliability of large-scale multi-GPU AI clusters that power frontier AI biology research: protein language models, genomic foundation models, and scientific reasoning systems built to be shared, not monetized. Our clusters run Slurm on Kubernetes infrastructure and support everything from day-to-day AI researcher workflows to multi-node hero training runs at thousands of GPUs. The team works at the intersection of AI tooling, distributed systems, HPC, and frontier AI, debugging deep AI infrastructure problems and building AI systems critical to the entire AI organization. The Opportunity CZ Biohub's mission is to cure or prevent all human disease. Achieving that requires training frontier-scale AI biology models, and that demands reliable, high-performance compute infrastructure. This is production engineering work at a frontier AI lab, with the twist that the mission is biology and the science is open. You'll keep GPU clusters running at high utilization, debug the toughest distributed systems failures, and build the operational foundations for scaling to multi-thousand GPU hero runs. The technical problems are genuinely hard (e.g., multi-node distributed training, InfiniBand fabrics, large-scale storage, Slurm at scale) inside an organization where the work is aimed at helping peop

pythonkubernetesgit
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