Principal Specialist – Data & Analytics Engineering - Lesaka ( FinTech) at Lesaka Technologies

Purpose

• The Principal Specialist: Data & Analytics Engineering is the technical authority within the Data Engineering team, responsible for shaping how data is engineered, transformed, and delivered across the Merchant Division.

This role ensures:

• High‑quality, scalable data architecture
• Consistent engineering standards and best practices
• Reliable, production‑grade data pipelines
• Alignment between engineering outputs and analytical needs
• Continuous improvement of the data platform

You are the technical conscience of the team — ensuring that every solution is built correctly, consistently, and sustainably.

Key Responsibility Areas

Technical Leadership & Architecture

• Own and define the end‑to‑end data platform architecture.
• Enforce engineering standards across pipelines, modelling, testing, CI/CD, and documentation.
• Lead architectural reviews and guide complex technical decisions.
• Identify and manage technical debt, scalability risks, and platform gaps.

Engineering Delivery

• Lead delivery of complex, high‑impact data engineering workstreams.
• Oversee multi‑source integrations and consolidation pipelines.
• Own analytics engineering practices — including transformation and semantic layers.
• Act as final technical reviewer for all production‑ready artefacts.
• Ensure alignment with Analytics & Insights for downstream consumption.

Mentorship & Capability Development

• Provide hands‑on technical mentorship to engineers.
• Lead code reviews, knowledge sharing, and best‑practice adoption.
• Support hiring and onboarding of new technical talent.
• Build and elevate team capability across data and analytics engineering.

Qualifications & Experience

Essential:

• Bachelor’s degree in Computer Science, Engineering, or related field
• 8+ years in data engineering and/or analytics engineering
• Proven experience as a technical lead or principal engineer
• Expertise in dbt or equivalent transformation tools
• Strong experience with cloud data platforms (Snowflake, BigQuery, Databricks)
• Advanced Python (pipelines, orchestration, testing)
• Advanced SQL (optimisation, complex transformations)
• Strong data modelling expertise (Kimball, Data Vault, OBT)
• Ability to communicate complex technical concepts to stakeholders

Advantageous:

• Financial services or fintech experience
• Multi‑entity or post‑acquisition data environments
• Streaming/event‑driven architecture exposure
• Data governance, lineage, and cataloguing tools

Closing Date 19 May 2026