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Thomson Reuters

Legal, financial data, and media services

Senior Privacy Engineer - Automation & Data Mapping

Data EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • The candidate must have 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.
  • The candidate must be proficient in at least one programming or scripting language, such as Python or SQL, and have demonstrated experience building and maintaining API integrations and automated workflows using tools such as Power Automate, custom scripts, or middleware.
  • The candidate must have hands-on experience integrating privacy management platforms such as OneTrust, BigID, or Collibra with internal ticketing, Azure DevOps, Jira, identity, and data-store systems, including field mapping, assignment logic, bidirectional status synchronization, and error handling.
  • The candidate must have experience designing and maintaining automated data discovery and mapping pipelines across structured and unstructured data sources, such as AWS Macie, Azure Purview, or database crawlers, that feed Records of Processing Activities (ROPA).
  • The candidate must have experience implementing risk-based conditional logic and trigger workflows for privacy assessments such as PIAs, DPIAs, or TIAs tied to intake or procurement systems.
  • The candidate must have experience building reporting and analytics pipelines, such as Azure DevOps Analytics or Power BI, that transform operational data into KPI dashboards for privacy program leadership.
  • The candidate must understand core privacy concepts including data minimization, purpose limitation, data subject rights, and retention, as well as global privacy regulations such as UK GDPR, EU GDPR, CCPA/CPRA, and PIPEDA, as applied to technical system design.
  • The candidate must have experience working with structured and unstructured data across multiple systems and cloud environments.
  • The candidate must be able to apply systems-design thinking to balance automation with defensibility and risk.
  • The candidate must be able to work independently and collaboratively across global engineering, legal, and privacy teams.
  • The candidate must have troubleshooting and debugging skills across integrated systems.
  • The candidate must be able to adapt to evolving regulatory and technical requirements.
  • The candidate must be able to communicate technical architecture clearly to nontechnical privacy and legal stakeholders.
  • Preferred: Experience with privacy management platforms such as OneTrust, BigID, or Collibra and their APIs or connector frameworks.
  • Preferred: CIPT certification.
  • Preferred: Experience with cloud data infrastructure such as AWS, Azure, or GCP, including native discovery and classification services such as Macie or Purview.
  • Preferred: Experience building automated redaction and exception-flagging pipelines with tuned accuracy and governed human-review checkpoints.
  • Preferred: Experience supporting DSAR automation at scale, including SLA tracking, escalation design, and volume-spike scaling strategies.
  • Preferred: Experience designing event-driven data-mapping architectures integrated with CMDB/asset inventory or cloud-discovery tooling.

Responsibilities

  • 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 such as OneTrust and internal systems, including ticketing, Azure DevOps, Jira, identity, and data stores; implement field mapping, assignment logic, bidirectional status synchronization, error handling, and logging to prevent systems from drifting apart.
  • Implement risk-based conditional logic and trigger workflows for privacy assessments such as PIAs, DPIAs, and TIAs tied to intake or procurement systems, including escalation paths for high-risk triggers and governance and audit trails for trigger rules.
  • Design and maintain automated redaction and exception-flagging pipelines, using approaches such as keyword or pattern matching and machine-learning classifiers, with a mandatory human-review checkpoint before release and an audit log of redaction decisions.
  • 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 tools such as OneTrust Data Discovery, BigID, Collibra, AWS Macie, Azure Purview, and database crawlers to feed classifications and data flows automatically into ROPA records.
  • Implement drift-detection mechanisms that reconcile ROPA records against discovery and mapping tool outputs, and support metrics such as the percentage of ROPA records reviewed within a defined window.
  • Support technical aspects of privacy impact assessments, including data-flow diagrams and system or architecture reviews.
  • Partner with engineering and product teams to implement privacy-by-design and privacy-by-default controls in products and internal systems.
  • Assist with technical implementation of data-retention and deletion requirements across structured and unstructured data sources.
  • Advise engineering teams on technical architecture considerations for new products and features from a privacy and data-protection perspective.
  • Build and maintain KPI dashboards and reporting pipelines, such as Azure DevOps Analytics and Power BI, to turn work-item and automation data into executive-ready privacy-program metrics, including DSAR SLA compliance, assessment backlog, and 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 and trigger-rule changes so metrics and workflows remain consistent and trustworthy over time.
  • 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, including triage automation and templated responses, to support DSAR volume spikes, and incorporate lessons learned into ongoing process improvements.
  • Support automation of assessment-intake quality through conditional required fields, real-time validation, and automated reminders to reduce incomplete submissions.

About the Company

Thomson Reuters

Legal, financial data, and media services

Thomson Reuters provides intelligent information and professional services for law, tax, finance, and media. It serves law firms, corporations, government agencies, and financial institutions with platforms like legal research (Westlaw), tax software (UltraTax CS), financial market data, and news services. These products are accessed through subscription-based platforms, ensuring ongoing updates and a steady revenue stream. The company also monetizes through advertising on media platforms and data analytics sales. It distinguishes itself by offering a broad, integrated suite of industry-specific tools combined with AI, cognitive computing, and machine learning to improve accuracy, efficiency, and predictive analytics in research and data insights. Its goal is to be a trusted partner that helps professionals make informed decisions by delivering reliable information and decision-ready tools while pursuing responsible, values-driven initiatives.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1851

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