Data Architect is responsible for designing and implementing the data architecture for core banking implementations. This role involves defining data strategies, developing data models, and ensuring data governance across all core banking platforms. The Data Architect will work closely with business stakeholders, IT teams, and external vendors to ensure that the data infrastructure is scalable, secure, and capable of supporting both operational and analytical needs.
Required Skills & Qualifications:
- Education: Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or a related field.
- Experience:
- 10+ years of experience as a data architect and expert in data modeling, and database design.
- Experience in strategizing, design and Integrating different data bases
- Data Management work experience in the environments where different data bases co-exist and Integrate with each other
- 5 years of experience working with any of the core banking systems-Transformation/Upgrade data migrations (e.g., Temenos, Oracle FLEXCUBE, Finacle,FIS).
- Experience with any one of the cloud-based data architectures and platforms (AWS, Azure, GCP).
- Strong background in data governance, data quality, and data security in a banking environment.
- Experience with ETL (Extract, Transform, Load) processes and tools (Informatica, Talend, etc.).
- Technical Expertise:
- Expertise in database technologies – DB2 and PostgreSQL
- Strong proficiency in data modeling tools
- Experience with big data technologies such as Hadoop, Spark, and Kafka.
- Knowledge of data warehousing and business intelligence tools (e.g., Power BI, Tableau).
- Familiarity with API integration and data interchange formats (e.g., XML, JSON).
- Strong understanding of regulatory and compliance frameworks in banking (e.g., PCI-DSS, GDPR, KYC, AML).
- Soft Skills:
- Strong communication skills, with the ability to explain complex data concepts to both technical and non-technical stakeholders.
- Excellent problem-solving and analytical skills.
- Collaborative mindset and ability to work in cross-functional teams.
Key Responsibilities:
- Data Architecture Design: Develop and maintain the overall data architecture for core banking systems, ensuring scalability, efficiency, and alignment with the organization's business goals.
- Data Modeling: Design and implement logical and physical data models for core banking applications, including customer data, transactions, accounts, payments, and regulatory reporting.
- Data Integration: Lead the integration of data across core banking systems and external platforms, ensuring data consistency, quality, and accessibility for real-time and batch processing.
- Data Strategy: Define and implement the data strategy for core banking, including data governance, data lifecycle management, and data retention policies.
- Data Quality & Governance: Establish and maintain data governance frameworks and ensure data quality management processes are in place. Work closely with data stewards to monitor data accuracy, completeness, and consistency.
- Data Security & Compliance: Implement data security measures, ensuring compliance with industry standards (e.g., PCI-DSS, GDPR) and regulatory requirements for banking data.
- Collaboration: Work closely with software developers, business analysts, and system architects to design data structures that support core banking processes and workflows.
- Cloud & Big Data Integration: Lead the migration and integration of data systems to cloud environments (AWS, Azure, GCP) and implement big data solutions as needed for advanced analytics and reporting.
- Data Reporting & Analytics: Support the development of reports and dashboards by ensuring the availability and integrity of data for business intelligence and decision-making processes.
- Performance Optimization: Monitor and optimize data systems for performance, ensuring efficient data retrieval and processing across core banking operations.
- Data Migration: Oversee data migration initiatives for core banking modernization projects, ensuring smooth transitions from legacy systems to modern platforms.
- Documentation: Create and maintain comprehensive documentation for data architectures, models, governance policies, and security protocols.