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United States of America; US - United States of America
Source: Yahoo careers · View original posting
From Yahoo's posting. “We” and “our” refer to the employer.
Yahoo serves as a trusted guide for hundreds of millions of people globally, helping them achieve their goals online through our portfolio of iconic products. For advertisers, Yahoo Advertising offers omnichannel solutions and powerful data to engage with our brands and deliver results.
A Little About Us
Yahoo's Privacy Legal team partners across the business—from advertising technology and AI, to media, communications, search, and commerce—to enable innovation while earning and maintaining user trust. We work alongside engineers, product managers, designers, data scientists, and business leaders from early product design through launch and ongoing operation.
Yahoo is seeking an experienced Privacy Technologist to help teams design, implement, and validate privacy-respectful systems and data practices across our advertising and media businesses.
You will work at the intersection of privacy, engineering, product, AI, identity, analytics, and advertising technology. You will turn privacy requirements and risk decisions into clear technical designs, control specifications, test plans, and reusable implementation patterns. This is a hands-on technical role that partners closely with privacy counsel; it is not primarily a legal-counsel position.
Responsibilites
Lead technical privacy reviews throughout the product lifecycle, from architecture and data-flow discovery through launch readiness and post-launch validation.
Map data flows and processing dependencies across web, mobile, connected TV, advertising platforms, APIs, SDKs, data pipelines, cloud services, and third-party integrations; review and/or produce clear system and data-flow diagrams.
Translate legal, policy, and product requirements into implementable technical controls, acceptance criteria, and engineering guidance in partnership with privacy counsel, product, security, and engineering teams.
Design and assess controls for data minimization, purpose limitation, consent and preference propagation, access, retention and deletion, sharing, de-identification, including user-rights and third party data-rights workflows.
Test and validate privacy controls using system documentation, logs, queries, network traces, configuration reviews, and other appropriate evidence; identify gaps and drive remediation to closure.
Assess advertising and identity technologies, including programmatic advertising, personalization, identity resolution, first-party data strategies, retail media, clean rooms, measurement, cookie alternatives, and evolving addressability solutions.
Evaluate consent and preference signals—including GPC, GPP, and IAB TCF—and help ensure they are collected, transmitted, interpreted, and enforced consistently across systems and partners.
Assess AI and machine-learning systems across the data lifecycle, including training and evaluation data, feature generation, inference, retrieval-augmented generation, agentic workflows, monitoring, and downstream use.
Evaluate privacy-enhancing technologies and de-identification approaches—including differential privacy, aggregation, tokenization, clean-room controls, and other context-appropriate techniques—while accounting for utility, operational constraints, and re-identification risk.
Build scalable privacy engineering patterns, playbooks, technical standards, review templates, and approved automation or AI-assisted workflows that help teams ship responsibly and efficiently.
Identify, test, and institutionalize emerging AI and automation tools to continuously replace repetitive manual reviews with automated compliance assertions and continuous validation pipelines.
Basic Qualifications
8+ years of experience in privacy engineering, privacy technology, security engineering, data governance, advertising technology, or another technical role involving complex data systems.
Demonstrated ability to review system architectures, trace end-to-end data flows, identify privacy risks, and recommend practical technical mitigations.
Working knowledge of modern web, mobile, API, cloud, and data-platform architectures, including client-side and server-side processing, cookies and local storage, mobile identifiers, SDKs, event pipelines, and data warehouses.
Hands-on ability to investigate data and system behavior using SQL and relevant technical tools; scripting experience in Python, JavaScript, or a comparable language is strongly preferred.
Experience designing or validating technical controls for consent, user preferences, minimization, retention and deletion, access, data sharing, and de-identification.
Strong understanding of privacy principles and major privacy and AI governance requirements, with the ability to collaborate with counsel and convert requirements into technical outcomes.
Experience with digital advertising, identity, measurement, consent frameworks, data collaboration, or other large-scale data ecosystems.
Ability to communicate clearly with engineers, product leaders, lawyers, data scientists, and business partners, including through concise diagrams, requirements, and risk explanations.
Sound judgment in ambiguous situations and a pragmatic, user-centered approach to balancing privacy risk, technical feasibility, product quality, and delivery speed.
Demonstrated experience assessing AI/ML architectures, including deep familiarity with data minimization in RAG pipelines, vector database access controls, training data governance, and model evaluation techniques.
Practical experience utilizing approved AI productivity and developer tools (e.g., GitHub Copilot, Gemini) to accelerate system analysis, script generation, and documentation synthesis.
Responsible and effective use of approved AI tools, including an understanding of confidentiality, security, validation, and accuracy limitations.
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