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Main Responsibilities:

1. Develop and maintain the organization’s overall data architecture, including data models, integration patterns, and workflows.
2. Define strategies for data storage, access, and processing, ensuring alignment with business objectives.
3. Create conceptual, logical, and physical data models to meet the organization’s data needs.
4. Ensure seamless integration of data from diverse sources, including databases, APIs, and real-time streaming systems.
5. Work with API and middleware teams to enable real-time and batch data sharing using standards-compliant protocols (e.g., REST, GraphQL).
6. Design systems to handle growing data volumes and high-performance requirements.
7. Optimize database performance, query execution, and data retrieval processes.
8. Implement data standards, policies, and best practices for data management and governance.
9. Collaborate with Information security teams to ensure data privacy, compliance, encryption, access controls, and data masking for shared datasets.
10. Implement robust data security frameworks to protect sensitive trade and compliance data during sharing and storage.
11. Ensure compliance with data privacy regulations.
12. Assess and recommend data management tools, technologies, and platforms (e.g., data warehouses, data lakes, cloud storage, analytics platforms).
13. Work closely with Data Engineers, Analysts, and Business Leaders to understand data requirements and translate them into architectural solutions.
14. Support teams in designing and implementing analytics and AI/ML solutions.
15. Document the data architecture, models, and processes to ensure clarity and accessibility for stakeholders.
16. Provide guidance and training to team members on data-related tools, technologies, and best practices.

Qualifications, Experience and Skills:

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or a related field.
• Proven experience as a Data Architect, with a strong track record in data modeling, architecture design, and data integration.
• Hands-on experience with databases (SQL/NoSQL), Data Warehouses, Data Lakes, and ETL/ELT tools.
• Proficiency in database technologies (e.g., Oracle, MS SQL Server, PostgreSQL, MySQL, MongoDB).
• Experience with big data tools (e.g., Hadoop, Spark, Kafka) 

Skills:

Oracle, ML Solutions, Communication Skills, Data Warehouse Architecture, Data Quality, SQL, Data Modeling,