M-Pesa Africa: Senior Data Architect

M-PESA Africa is looking for a Senior Data Architect to design, govern, and evolve our enterprise data landscape across our markets. Operating at the intersection of mobile money, payments infrastructure, AI, and analytics, you will set the architectural standards and strategic direction for how data flows, is governed, and generates value across M-PESA's platforms.

This is a senior individual contributor role with broad influence across engineering, product, compliance, and group-level stakeholders. You will be expected to lead with vision, mentor others, and translate complex data challenges into scalable architectural solutions.

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.