Data Governance & Privacy Lead
Skills
About This Role
Data Governance & Privacy Lead
defines and drives the governance framework for data used by smart-city capabilities (including Cognitive AI).
The role establishes standards for
data classification, privacy-by-design, consent, retention, lineage, and controlled sharing
across multi-tenant environments and multiple vendors.
Working with stakeholders, security teams, and delivery vendors, the lead ensures that
data products and AI pipelines comply with applicable regulations and policies
, and that governance is operationalized through tooling, processes, and automated controls embedded into platform onboarding and service delivery.
Key Responsibilities
- Define
- data governance operating model
- : roles (data owners/stewards), RACI, councils, and approval workflows.
- Establish standards for
- data classification, residency, retention, legal holds, and secure disposal
- across tenants.
- Define
- privacy-by-design requirements
- : consent management, purpose limitation, minimization, and data access controls.
- Drive
- data cataloging and metadata management
- (ownership, descriptions, schemas, sensitivity labels, quality scores).
- Define
- lineage and provenance requirements
- for data pipelines and AI artifacts (datasets, labels, embeddings, vector indexes).
- Specify
- DLP and egress control requirements
- for storage, APIs, and AI/RAG workflows; coordinate with Cybersecurity Architect.
- Define
- data-sharing policies and contracts
- (inter-agency sharing, vendor access boundaries, anonymization/masking rules).
- Establish
- data quality framework
- : validations, monitoring, SLA/KPIs, issue management, and remediation processes.
- Provide
- governance assurance for vendor deliverables
- (design reviews, acceptance criteria, compliance evidence packs).
- Enable
- operations
- : governance dashboards, audit reporting, periodic access reviews, and training for data owners/stewards.
Skills & Abilities
- Strong knowledge of
- data governance, privacy, and compliance practices
- in regulated environments.
- Ability to
- operationalize governance
- through processes and automated technical controls (policy-as-code mindset).
- Understanding of
- modern data platforms
- (lakehouse, streaming, catalog/lineage) and
- AI data lifecycle
- (RAG/embeddings).
- Excellent
- stakeholder management
- across legal, security, business owners, and vendor teams.
- Strong
- documentation, control definition, and audit-readiness skills
- .
Education & Experience
- Bachelor’s degree in
Computer Science, Information Technology, Cybersecurity
- ; Master’s degree highly preferred.
- **7+ years**
- in data governance, privacy, compliance, or data management roles (government/telco preferred).
- Experience implementing
- data catalog/lineage tools
- and defining enterprise-wide data standards and policies.
- Experience with
- privacy controls
- (consent, RTBF/DSR processes, anonymization/masking, retention schedules).
- Background working with
- delivery vendors
- and integrating governance into program delivery and acceptance gates.
- Familiarity with
- AI data governance concepts
- (dataset/model cards, provenance, RAG content governance).
Preferred Tools
- **Data governance/catalog:**
- Microsoft Purview (or equivalent), data classification/labeling tools
- **Data protection:**
- DLP tooling, encryption/CMK/HSM, key management (Key Vault/KMS)
- **Data platforms:**
- lakehouse (Delta/Iceberg), streaming (Kafka/Event Hubs), SQL/ETL orchestration (Airflow)
Soft Skills
- Strong
- facilitation and consensus-building
- (data councils, policy workshops)
- Ability to
- translate legal/privacy requirements into actionable technical controls
- High
- attention to detail
- with pragmatic prioritization
- Confidence to
- challenge non-compliant designs
- and drive remediation
- Effective
- communication and training approach
- for non-technical stakeholders
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