Senior Privacy Engineer Job at 1Password

Senior Privacy Engineer

1Password

Location:
United States; Canada

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

153000.00 - 214000.00 USD; CAD / Year

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Job Description:

We are excited to welcome a Senior Privacy Engineer to join 1Password. Our mission is to build products people trust—and privacy is a core part of that trust. In this role, you’ll bring strong data engineering / big data systems experience to help us build and operate privacy-preserving data practices at scale, especially across data ingestion, governance, and pipeline processing in a modern SaaS environment. As part of the Privacy Engineering group (within GRC and Security, and in close partnership with Engineering, Product, Data, and Legal/Privacy), you’ll help shape how we collect, process, store, access, and delete data across services, telemetry, analytics, support tooling, third-party integrations, and emerging AI/ML solutions—translating privacy requirements into durable engineering controls.

Job Responsibility:

Work on privacy engineering problems where data scale and data systems matter: pipelines, telemetry/analytics, and data stores that support business needs while maintaining strong privacy protections
Build practical controls for data access governance and obfuscation in large datasets (policy enforcement, row/column controls, masking/tokenization, privacy-aware query patterns)
Improve retention/deletion and logging/telemetry hygiene so privacy remains strong as systems evolve
Help enable privacy-safe AI/ML use by implementing controls, infrastructure, and analysis that reduce data exposure and support responsible product development
Collaborate across teams to make privacy the default through templates, guardrails, and automation
Build privacy-by-design into data systems and pipelines
Partner with Product and Legal/Privacy to translate requirements (e.g., DPIAs/PIAs, consent, data subject rights) into concrete technical controls and deliverable plans
Influence how we design and evolve data ingestion and processing pipelines, ensuring privacy-safe collection and downstream use
Help teams implement privacy-safe patterns for data flows, access boundaries, and storage decisions
Implement scalable access controls and data protection in large datasets
Design and implement policy-based access controls for analytics and data platforms, including row/column-level controls where appropriate
Build or improve data obfuscation layers (e.g., tokenization, masking, pseudonymization) and define privacy-aware query patterns that reduce exposure while preserving utility
Partner with data/platform teams to ensure controls are reliable, testable, and operationally supported
Enable privacy-safe AI/ML solutions
Partner with product and engineering teams to design privacy-safe data flows for AI/ML use cases, including training, evaluation, and inference
Implement guardrails that support safe data use in AI/ML systems (e.g., minimization, access controls, dataset curation, logging/telemetry hygiene, retention/deletion alignment)
Contribute to reviews and analysis that assess privacy risk in AI/ML solutions (e.g., data provenance, leakage risks, and appropriate protections for sensitive data)
Improve lifecycle controls and telemetry hygiene
Strengthen retention and deletion across production databases, logs, analytics, backups, and relevant third-party systems
Improve observability and telemetry practices by tightening protections and ensuring collection remains consent-aware
Lead through hands-on execution and collaboration
Provide technical leadership through code reviews, design reviews, and pragmatic guidance across multiple teams
Contribute to privacy tooling, service templates, and CI/CD automation that prevent regressions and make safe choices easy

Requirements:

5+ years of experience in software engineering, data engineering, or data analytics at SaaS companies, with a strong emphasis on data ingestion, governance, and pipeline processing
Demonstrated expertise building and operating production systems at meaningful scale, including debugging, reliability, and operational ownership
Experience implementing data access control and data obfuscation layers on top of data lakes or large analytics environments, including policy-based access, row/column-level controls, tokenization/masking, and privacy-aware query patterns
Experience implementing these controls via commodity governance/authorization offerings (e.g., Databricks Unity Catalog, Okera, Privacera, or similar technologies), including integration into real-world data workflows and enforcement paths
Experience performing analytics and investigations using Python and SQL (e.g., validating data minimization, measuring collection changes, auditing datasets, and supporting privacy reviews)
Experience building or supporting privacy-safe controls, infrastructure, and analysis for AI/ML solutions (e.g., data provenance and curation, access controls around training/evaluation datasets, inference telemetry hygiene, retention/deletion alignment, and practical mitigations for leakage risk)
Familiarity with DLP-style controls and privacy-aware analytics patterns
Proficiency in one or more backend languages (e.g., Go, Rust, Java, TypeScript) and a track record of delivering production-quality code
Practical privacy engineering experience implementing controls such as minimization, access controls, encryption, retention/deletion, and privacy-safe analytics/telemetry
Ability to translate privacy requirements (GDPR / CCPA / CPRA concepts) into engineering work without relying on “paper compliance”
Strong cross-functional communication skills and comfort partnering with Product, Legal/Privacy, Security, Data, and Engineering teams

Nice to have:

Experience building data governance platforms (classification, catalogs, automated retention/deletion, policy enforcement)
Experience with distributed systems and their operational tradeoffs (availability, performance, observability, rollout safety)
Security company experience or familiarity with threat modeling and secure development practices
Familiarity with compliance/security frameworks and audits (e.g., ISO 27001, ISO 27701, SOC 2) in ways that translate into real engineering controls

What we offer:

Health and wellbeing: Maternity and parental leave top-up programs
Competitive health benefits
Generous PTO policy
Growth and future: RSU program for most employees
Retirement matching program
Free 1Password account
Community: Paid volunteer days
Peer-to-peer recognition through Bonusly
Remote-first work environment

Additional Information:

Job Posted:
February 21, 2026

Employment Type:

Fulltime

Work Type:

Remote work

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