Data Governance Engineer: Audit-Ready & Compliance

arabic; Riyadh; On-site; SAR 180,000 - 300,000; Full time

Job summary

arabic seeks a data governance expert to ensure governance across data catalog, lineage, metadata, and quality reporting in a regulatory context. You will collaborate with engineers and the auditing team to prove compliance with Saudi data rules.

You will define quality rules, classify datasets, maintain governance documents, and guide privacy measures for data and ML systems, while preparing audit evidence.

Qualifications

• Experience implementing national data-management and personal-data-protection requirements (e.g., NDPM/PDPL).
• Ability to design and publish data-quality rules and quality reports.
• Proficiency in data catalog, lineage, and metadata tooling.
• Knowledge of data classification schemes and access design (RBAC, least privilege).
• Experience writing formal governance documents and audit evidence.

Responsibilities

• Stand up and run the data catalog, lineage and metadata capture across all pipelines and models.
• Define data-quality rules, enforce them, and publish validation and quality reports.
• Classify datasets under the client’s scheme and specify access rules for levels.
• Keep governance documents current: architecture updates, data models, lineage, catalog, metadata, quality, security and access.
• Advise data and ML engineers on privacy: masking, de-identification, retention.
• Prepare evidence for client and regulator audits and write governance sections of architecture documents.

Skills

Data governance

Data catalog

RBAC

Privacy

Audits

SQL

Education

DAMA CDMP

Tools

Google Data Catalog

Dataplex

Job description

arabic seeks a data governance expert to ensure governance across data catalog, lineage, metadata, and quality reporting in a regulatory context. You will collaborate with engineers and the auditing team to prove compliance with Saudi data rules.

You will define quality rules, classify datasets, maintain governance documents, and guide privacy measures for data and ML systems, while preparing audit evidence.