Description:
This role is ideal for professionals who have expertise in data integration, governance, cloud platforms, semantic modeling, and regulatory compliance frameworks (NDMO, PDPL, etc.). You will play a critical role in building an advanced data framework that ensures data accessibility, security, and actionable insights.
Key Responsibilities:
- Design and implement a unified data architecture (data fabric) integrating disparate systems while eliminating data silos.
- Lead the development of data governance frameworks, ensuring high-quality, secure, and compliant data usage.
- Oversee the deployment of real-time data integration pipelines and ensure proper orchestration of data flows.
- Develop and implement semantic data models for intuitive data consumption and advanced visualization.
- Work closely with business and technical stakeholders to ensure regulatory compliance (NDMO, PDPL) and seamless adoption of data practices.
- Ensure robust data security, access control, and encryption policies.
- Collaborate with data engineers to design and deliver advanced analytics tools, predictive modeling, and business intelligence capabilities.
- Provide ongoing training and documentation for technical and non-technical stakeholders.
- Conduct risk assessments and devise mitigation plans for data protection, migration, and integration challenges.
Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
- Minimum 8+ years of experience in data architecture, data integration, or enterprise-level data systems implementation.
- Strong expertise in data governance frameworks, cloud-based data solutions (e.g., Oracle, Azure, AWS), and data privacy regulations.
- Proven ability to design and implement ETL pipelines, data orchestration, and streaming solutions.
- Experience working with data lakes, warehouses, and lakehouses.
- Understanding of semantic modeling, APIs, data cataloging, and lineage tracking.
- Familiarity with machine learning or AI within large-scale data ecosystems.
- Excellent problem-solving and stakeholder engagement skills.
- Strong background in ensuring compliance with data privacy frameworks.