Bachelor&aposs or Master&aposs degree in Computer Science, Data Science, Information Systems, or a related discipline.
8+ years of experience in data architecture, preferably in banking, fintech, or financial services.
Design and implement enterprise-wide data architecture for core banking, payments, credit risk, anti-fraud, and regulatory reporting platforms.
Develop and maintain enterprise data models aligned with financial product lifecycles (loans, deposits, derivatives, etc.).
Establish and enforce data governance frameworks, metadata management, and data lineage documentation to meet internal audit and external regulatory standards.
Lead the modernization of legacy data systems into cloud-native architectures (e.g., Snowflake, Azure Data Lake, AWS Redshift).
Collaborate with Compliance, Risk, Treasury, and Finance teams to ensure accurate data aggregation and reporting.
Define and guide standards for ETL/ELT pipelines, master data management (MDM), and data quality assurance.
Support the implementation of data privacy, retention, and security policies in line with regulatory mandates (e.g., GDPR, CCPA, local data residency laws).
Review and validate third-party vendor integrations, APIs, and open banking standards from a data architecture perspective.
Provide technical leadership on strategic initiatives such as real-time fraud detection, credit decisioning engines, and customer 360 analytics.
Experience with Oracle , Sql Server , Postgres and No SQL Databases
Strong knowledge of financial domain data structures (loans, accounts, transactions, KYC, AML, risk models).
Expertise in data modeling, data warehousing (e.g., Oracle, Teradata, Snowflake), and cloud data platforms.
Experience with data governance tools and practices (e.g., Collibra, Informatica, Apache Atlas).
Proficiency in SQL, data pipeline orchestration, and integration technologies (e.g., Kafka, Talend, Airflow).
Knowledge of regulatory requirements (Basel II/III, IFRS 9, BCBS 239, FATCA) and their data implications
