Data Governance Consultant

• Lead solutioning and implementation of data governance models across business and IT stakeholders.
• Conduct system inventory and documentation of Oracle-based and related platforms.
• Map data flows, dependencies, and relationships across complex multi-domain environments.
• Reverse engineer existing Oracle schemas, ERDs, tables, PK/FK relationships, triggers, and packages.
• Design conceptual, logical, and physical data models.
• Establish and maintain metadata repositories and source catalogues.
• Execute data profiling and implement data quality reporting (completeness, consistency, duplicates).
• Define governance models aligned with GDPR, AVG, and BIO regulations.
• Design migration and integration strategies, including phased migrations and API-driven integrations.
• Support cloud migrations and lakehouse architectures using Snowflake and Databricks., * Translate business requirements into structured data models and governance frameworks.
• Analyse and optimise legacy database structures.
• Identify data quality issues and implement corrective strategies.
• Design secure data classification and retention frameworks.
• Align architecture decisions with regulatory and compliance standards.
• Plan and execute data migration strategies with validation and quality controls.
• Collaborate effectively across IT, business, and governance teams.
• Ensure performance optimisation during cloud and hybrid transitions.

What we bring to the table:

• Opportunity to work on complex, large-scale data transformation initiatives.
• Exposure to cloud migration and modern lakehouse architectures.
• Engagement in governance-driven and compliance-focused environments.
• Collaboration with cross-functional technical and business stakeholders.
• Challenging projects in structured and regulated sectors.

• 8-10 years of hands-on experience in data governance, data modelling, and architecture.
• Strong expertise in Oracle databases, schema analysis, and ERD interpretation.
• Experience with data migrations and integration in hybrid and cloud environments.
• Proficiency in BI tools such as Power BI and Tableau.
• Working knowledge of Snowflake and Databricks lakehouse platforms.
• Experience in data profiling, quality management, and metadata management.
• Understanding of Data Vault, Dimensional Modelling, and Data Mesh principles.
• Exposure to ETL/ELT processes and collaboration with Data Engineers.
• Knowledge of Kafka, Oracle GoldenGate, and API-based integrations.
• Familiarity with public sector environments and compliance-driven ecosystems.