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RNAIPL - Data Governance Specialist

NISSAN RENAULT FINANCIAL SERVICES INDIA PRIVATE LI
Multiple Locations
6 - 10 Years
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3.8white-divider87+ Reviews

Posted on: 12/01/2026

Job Description

Description:


Key Responsibilities :


Data Quality Management :


- Define, refine, and institutionalize enterprise-wide data quality standards (accuracy, completeness, consistency, timeliness).

- Design and roll out data quality scorecards and dashboards aligned to AMIEO business KPIs.


- Drive root-cause analysis and remediation workflows in coordination with business data owners and stewards.

- Establish a sustainable issue management and escalation framework for recurring quality gaps.

Policy & Standards Development :


- Support the creation and continuous improvement of Nissans enterprise data policies (e. privacy, lifecycle management, metadata handling).

- Embed governance checkpoints and policies into digital delivery and transformation frameworks.

- Design simple playbooks, guides, and training sessions to enhance awareness and adoption of data best practices across functions.

- Collaborate with central data governance teams in Japan and other regions to ensure harmonization and avoid redundancy.

Regulatory & Compliance Readiness :


- Support Nissans implementation of EU Data Act, GDPR, and upcoming AI Act across applicable use cases (e. vehicle data sharing, AI model traceability).

- Liaise with Nissans legal, audit, and risk functions to map responsibilities and action plans.

- Assist in maintaining Nissans compliance posture- create documentation, audit support, and breach preparedness materials.

- Help define compliant data-sharing processes with third parties, partners, and regulators, especially in relation to vehicle, user, and telemetry data.

Key Qualifications :


- 6-10 years of experience in data governance, regulatory compliance, or data quality roles, ideally within automotive, manufacturing, or tech sectors.

- Familiarity with frameworks such as DAMA-DMBOK, ISO 8000, EU Data Act, GDPR, and AI governance frameworks.

- Good understanding of modern data architectureideally AWS, Snowflake, Microsoft Purview/Fabric.

- Proven track record of working in cross-functional environments with business, legal, and data teams.

- Comfortable operating in lean, high-accountability roles with limited external dependencies.


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