Key Responsibilities

• Implement privacy-enhancing techniques (PETs) such as k-anonymity, l-diversity, t-closeness and differential privacy across data pipelines and analytics systems.
• Design and enforce PII minimisation strategies to ensure only necessary personal data is processed and exposed.
• Implement data anonymisation, pseudonymisation and masking techniques across datasets and data products.
• Support secure access control models in collaboration with Cybersecurity, Platform and Cloud Engineering teams.
• Ensure end-to-end data lineage tracking and auditability across data pipelines and analytics workflows.
• Embed privacy-by-design principles into data ingestion, transformation, feature engineering and ML pipelines.
• Support compliance with internal governance frameworks, including Data Sharing and Monetisation Policy approvals.
• Collaborate with Data Engineers, MLOps Engineers, Big Data Engineers and API Dev...