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SAFARICOM
Telecommunications
Description
Qualifications
- Education:
- Bachelor's degree in Computer Science, Information Systems, Electrical/Computer Engineering, or a related field.
- Bachelor's degree in Computer Science, Information Systems, Electrical/Computer Engineering, or a related field.
- Experience:
- Experience in data architecture, data engineering, or closely related technical disciplines, with at least 3 years in a senior or lead capacity.
- Proven track record designing enterprise-scale data platforms in financial services, fintech, or telecommunications.
- Deep expertise in data modelling (conceptual, logical, physical) for both OLTP and OLAP systems.
- Hands-on experience with cloud data platforms (AWS, GCP, or Azure) and big data technologies (Spark, Databricks, BigQuery, Redshift, etc.).
- Proficiency in data integration patterns: ETL/ELT, Change Data Capture (CDC), event streaming, and API-driven data exchange.
- Strong understanding of data governance frameworks and tools (DAMA-DMBOK, Apache Atlas, Collibra, or equivalent).
- Experience with streaming platforms such as Apache Kafka in high-throughput transactional environments.
- Experience in data architecture, data engineering, or closely related technical disciplines, with at least 3 years in a senior or lead capacity.
Responsibilities
- Data Architecture & Strategy
- Own the enterprise data architecture across M-PESA Africa's multi-market environment, spanning transactional, operational, analytical, and AI/ML data domains.
- Define and enforce data modelling standards, data flow patterns, and integration architecture for real-time and batch processing pipelines.
- Lead architecture design for data platforms supporting payment rails, API analytics, fraud and AML detection, and regulatory reporting.
- Drive the transition to modern data architectures: data mesh, data lakehouse, event-driven patterns aligning to M-PESA's cloud and hybrid infrastructure strategy.
- Own the enterprise data architecture across M-PESA Africa's multi-market environment, spanning transactional, operational, analytical, and AI/ML data domains.
- Data Governance & Standards
- Establish and champion enterprise-wide data governance frameworks, data quality standards, and master data management (MDM) policies across all six markets.
- Define data classification, lineage, and cataloguing standards, ensuring traceability from source systems (e.g., Fintech 2.0 Platform) through to consumption layers.
- Partner with Compliance, Legal, and Market teams to ensure data architectures meet local regulatory obligations and cross-border data sovereignty requirements.
- Establish and champion enterprise-wide data governance frameworks, data quality standards, and master data management (MDM) policies across all six markets.
- Integration & Platform Architecture
- Architect data integration patterns between M-PESA core systems, third-party platforms and analytics/AI layers.
- Collaborate with API gateway teams to define event-driven, API-first data exchange patterns aligned with the integration layer strategy.
- Design and govern streaming and CDC pipelines using technologies such as Apache Kafka and Oracle GoldenGate across market-level deployments.
- Architect data integration patterns between M-PESA core systems, third-party platforms and analytics/AI layers.
- AI & Analytics Enablement
- Design data architectures that underpin AI/ML use cases including transaction monitoring, watchlist screening, customer intelligence, and predictive analytics.
- Define feature store design, data pipeline standards, and model serving infrastructure patterns for production ML workflows.
- Partner with the AI/ML team to evaluate and onboard vector databases, embedding pipelines, and LLM-ready data infrastructure.
- Design data architectures that underpin AI/ML use cases including transaction monitoring, watchlist screening, customer intelligence, and predictive analytics.
- Leadership & Stakeholder Engagement
- Serve as the senior data architecture voice in Architecture Review Boards, design forums, and group-level governance bodies.
- Mentor and coach mid-level data engineers and architects across markets, building data architecture capability within the team.
- Produce executive-ready architecture artefacts, including C4/Mermaid diagrams, ADRs, and data strategy presentations for CTO/CIO audiences.
- Lead vendor evaluations for data platform tools, cloud data services, and governance technologies.
- Serve as the senior data architecture voice in Architecture Review Boards, design forums, and group-level governance bodies.
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