Safaricom is the leading provider of converged communication solutions in Kenya. In addition to providing a broad range of first-class products and services for Telephony, Broadband Internet and Financial services, Safaricom seeks to uplift the welfare of Kenyans through value-added services and support for community projects.

M-Pesa Africa: Senior Data Architect

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.

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.

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.

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.

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.

Qualifications

Education:

• 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.

• 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.
• 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.
• 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.
• 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.
• 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.

• Data modelling (conceptual, logical, physical)
• Cloud data platforms (AWS, GCP, or Azure)
• Big data technologies (Spark, Databricks, BigQuery, Redshift, etc.)
• Data integration patterns (ETL/ELT, Change Data Capture (CDC), event streaming, API-driven data exchange)
• Data governance frameworks and tools (DAMA-DMBOK, Apache Atlas, Collibra, or equivalent)
• Streaming platforms (Apache Kafka)

• Bachelor's degree in Computer Science, Information Systems, Electrical/Computer Engineering, or a related field.
• 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.