To design, implement, govern, and continuously optimize the Bank’s enterprise data architecture, data warehousing, and advanced analytics platforms, ensuring data integrity, availability, security, regulatory compliance, and business value realization. The role is responsible for the entire data lifecycle, from sourcing and integration through analytics, reporting, and regulatory compliance.

Data Architecture & Warehousing

• Design and maintain the Bank’s enterprise data architecture, covering CBS, digital channels, cards, treasury, payments, agency banking, and external integrations.
• Lead the development and management of the Enterprise Data Warehouse (EDW) and data marts.
• Define data models (conceptual, logical, physical) to support operational, analytical, and regulatory reporting.
• Ensure scalable, high-performance data platforms supporting real-time and batch processing.
• Align data architecture with cloud and hybrid infrastructure strategies.

Data Integration & Engineering

• Oversee ETL/ELT pipelines, APIs, streaming, and ingestion frameworks.
• Ensure reliable integration of structured and unstructured data sources.
• Manage data quality controls at ingestion, transformation, and consumption stages.
• Work closely with Integration teams to ensure data consistency.

Advanced Analytics Enablement

• Provide the foundational data platforms for:
• Advanced analytics
• AI/ML model development
• Predictive and prescriptive analytics
• Enable self-service analytics for business users while maintaining governance.
• Support analytics use cases including: Customer behavior, Credit risk, Fraud detection, Treasury and, liquidity analytics, Operational efficiency dashboards, Support predictive and prescriptive analytics use cases

Data Governance & Compliance

• Establish and enforce Data Governance Frameworks (data ownership, stewardship, classification)

Establish and enforce data governance frameworks, including:

• Data ownership and stewardship
• Metadata management
• Master Data Management (MDM)

• Define and monitor data quality metrics (accuracy, completeness, timeliness, consistency)

Ensure compliance with:

• Bank of Tanzania (BoT) regulations
• AML/KYC data requirements
• Data protection and privacy laws
• ISO 27001 / ISO 22301
• PCI DSS (where applicable)

• Support internal and external audits by providing traceable, accurate, and secure data.

Ensure data retention and archival policies are enforced

Security, Privacy & Access Control

Work with Cybersecurity & SOC teams to enforce:

• data encryption (at rest and in transit)
• role-based access control (RBAC)
• least-privilege principles
• secure data sharing & masking

• Ensure secure handling of PII, financial, and customer data.

• Participate in incident response related to data breaches or integrity issues.

Reporting & Regulatory Support

Ensure timely and accurate delivery of:

• Regulatory reports
• Management dashboards
• Financial and operational analytics

• Support IFRS, Basel, AML, and other supervisory reporting requirements.

• Maintain a single source of truth for enterprise reporting.

Stakeholder & Cross-Functional Collaboration

Act as the primary data partner to:

• Operations
• ICT
• Risk & Compliance
• Finance
• Business Units

• Translate business requirements into scalable data solutions.

• Provide expert guidance on data-related decision making.

Leadership & Capacity Building

• Lead, mentor, and develop data engineers, BI developers, and data analysts.
• Build internal capability in data engineering, analytics, and governance.
• Manage vendors and third-party data service providers.

Education

• Bachelor’s degree in computer science, Information Systems, Data Science, or related field.
• Professional certification in Data Management, Analytics, or ICT is an added advantage.

Technical Skills

• Data warehousing platforms (on-prem, cloud, or hybrid) & Lakehouse platforms.
• ETL/ELT tools and data integration frameworks.
• SQL, data modeling, and performance optimization.
• BI and analytics tools.
• Knowledge of AI/ML data pipelines (foundational).
• Data governance and metadata tools.
• Security, encryption, and access control concepts

Experience

• 3–5 years experience in data architecture, data warehousing, or analytics in a regulated environment.

Strong experience in:

• Enterprise data warehousing
• Banking or financial services data
• Regulatory reporting environments
• Exposure to AI/ML data pipelines is highly desirable.

Behavioral & Leadership Competencies

• Strong analytical and problem-solving skills
• High attention to detail and data accuracy
• Ability to challenge and enforce standards
• Stakeholder management and communication
• Regulatory and risk awareness
• Strategic thinking with execution focus.

• Problem Solving skills

• Good Analytical Skills

• Communication Skills