Job Description

The Privacy Operations Engineer bridges privacy compliance and technical implementation, architecting, building, and maintaining the tooling, automation, and data infrastructure that powers the company's global privacy program across UK/EU, US, APAC, and other regions. This role works closely with engineering and product teams to operationalize privacy-by-design and privacy-by-default requirements, and owns the technical backbone connecting privacy management platforms (e.g., "OneTrust"), work-management systems (e.g., Azure DevOps, Jira), and the organization's broader data and cloud infrastructure. This is a hands-on engineering role requiring both strong technical depth and working knowledge of global privacy regulatory concepts.

Key Responsibilities

- Privacy Automation Engineering Design, build, and maintain automation for privacy operations workflows, including data subject rights fulfillment, data discovery, data mapping, and privacy assessment triggering.
- Build and maintain API and Power Automate integrations between privacy management platforms (e.g., "OneTrust") and internal systems (ticketing/ADO/Jira, identity, data stores), including field mapping, assignment logic, bi-directional status sync, and error handling/logging so systems do not drift apart.
- Implement risk-based conditional logic and trigger workflows for privacy assessments (PIAs/DPIAs/TIAs) tied to intake or procurement systems, including escalation paths for high-risk triggers and governance/audit trails over the trigger rules themselves.
- Design and maintain automated redaction and exception-flagging pipelines (e.g., keyword/pattern matching, ML classifiers) for DSAR fulfillment,



ensuring a mandatory human-review checkpoint before release and maintaining an audit log of redaction decisions.
- Data Mapping & ROPA Infrastructure Build and maintain an automated, event-driven data flow inventory and data mapping pipeline, tied to system/vendor intake and procurement processes rather than periodic manual surveys.
- Build and maintain integrations with data discovery and classification tooling (e.g., OneTrust Data Discovery, BigID, Collibra, AWS Macie, Azure Purview, database crawlers) to automatically feed classifications and data flows into ROPA records.
- Implement drift-detection mechanisms that reconcile ROPA records against discovery/mapping tool outputs, and support metrics such as percentage of ROPA records reviewed within a defined window.
- Support technical aspects of privacy impact assessments, including data flow diagrams and system/architecture review.
- Privacy-by-Design & Product Collaboration Partner with engineering and product teams to implement privacy-by-design and privacy-by-default controls within products and internal systems. Assist in the technical implementation of data retention and deletion requirements across structured and unstructured data sources. Advise engineering teams on technical architecture considerations for current products and features from a privacy and data protection perspective.
- Program Tooling, Reporting & Observability Build and maintain KPI dashboards and reporting pipelines (e.g., ADO Analytics,



Power BI) that translate raw work-item and automation data into executive-ready privacy program metrics (DSAR SLA compliance, assessment backlog, incident response times). Monitor and report on the health of privacy tooling and automated processes, troubleshooting integration or data-quality issues as they arise. Maintain governance over report definitions and automation/trigger rule changes so metrics and workflows remain consistent and trustworthy over time.
- DSAR & Assessment Automation at Scale Design and maintain automated routing of DSAR tasks with data-owner mapping across multiple systems, SLA tracking tied to statutory deadlines, and tiered escalation as deadlines approach. Build scalable automation and surge-capacity mechanisms (triage automation, templated responses) to support DSAR volume spikes, incorporating lessons learned into ongoing process improvements. Support automation of assessment intake quality, including conditional required fields, real-time validation, and automated reminders to reduce incomplete submissions.

Required Qualifications

- 5-7+ years of experience in a data engineering, software engineering, or technical privacy/compliance engineering role, ideally supporting privacy or compliance operations at a global or multinational organization.
- Strong proficiency in at least one programming/scripting language (e.g., Python, SQL) and demonstrated experience building and maintaining API integrations and automated workflows (e.g., Power Automate, custom scripts, middleware).
- Hands-on experience building integrations between privacy management platforms (e.g., "OneTrust", BigID, Collibra) and internal systems (ticketing/ADO/Jir

📌 Privacy Operations Engineer (Toronto)
🏢 CAN002 Thomson Reuters Canada
📍 Toronto