Vice President - Data Architect & Data Engineering - Bank

A Data Architect and Data engineer is a seasoned professional responsible for developing and optimizing database models to store and retrieve company information. The Data Architect focuses on the strategic aspects of data management, ensuring data integrity, security, and efficient utilization. This role is pivotal in shaping the bank's data landscape, driving innovation, and enabling data-driven decision-making.

Key Responsibilities:

Enterprise Data Warehouse (EDW) Management:

- Design: Define the architecture, schema, and data models for the EDW, ensuring scalability, performance, and flexibility to accommodate evolving business requirements.

- Development: Keep evolving the EDW with continuous improvement.

- Maintenance: Regularly monitor and optimize the EDW environment to ensure optimal performance, data quality, and reliability. This includes tasks such as data cleansing, indexing, and partitioning.

- Business Reports: Generation of reports for various business functions including sales, product, collection, finance, risk management, and customer service.

- Customization of reports to meet specific business requirements and KPIs, providing stakeholders with actionable insights and performance metrics.

Inter-System Data Connectivity:

- Integration Architecture: Design and implement data integration architectures (e.g., ETL pipelines, API gateways) to enable seamless data exchange and interoperability between disparate systems, databases, and applications.

- Data Mapping and Transformation: Define data mappings, transformations, and business rules to reconcile schema differences and ensure data consistency and integrity across integrated systems.

- Real-Time Data Streaming: Implement real-time data streaming solutions (e.g., Apache Kafka, Apache Flink) to enable continuous data ingestion and processing for use cases such as fraud detection, real-time analytics, and personalized customer experiences.

Data Governance Leadership:

- Policies and Standards: Develop and document data governance policies, standards, and procedures covering data classification, access controls, data lineage, metadata management, and data retention.

- Compliance: Ensure adherence to regulatory requirements (e.g., GDPR, CCPA, Basel III) and industry standards (e.g., ISO 27001, NIST) by implementing appropriate controls and conducting regular audits and assessments.

- Training and Awareness: Provide training and awareness programs to educate stakeholders about the importance of data governance, their roles and responsibilities, and best practices for data management.

Privacy and Security Oversight:

- Data Privacy: Implement privacy-enhancing techniques such as data anonymization, encryption, and access controls to protect sensitive information from unauthorized access or disclosure.

- Security Measures: Deploy robust security measures including firewalls, intrusion detection/prevention systems, and multi-factor authentication to safeguard data assets against cyber threats and breaches.

- Regulatory Compliance: Stay abreast of evolving privacy and security regulations and ensure that the organization remains compliant with all applicable laws and regulations.