Analytics Engineer II

Capitec

Stellenbosch

On-site

ZAR 900,000 - 1,350,000

Full time

6 days ago
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Job summary

Capitec Ltd is seeking an Analytics Engineer II in Stellenbosch to bridge data engineering and analytics, building clean, trusted data assets and scalable pipelines. You’ll collaborate with data architects and analysts to design models aligned with enterprise strategy and drive decision‑making across the organisation.

The role emphasizes governance, reliable data assets and modern tooling, including Airflow and CI/CD practices, to deliver rapid, accurate insights for business stakeholders.

Qualifications

  • 5-8+ years in analytics engineering or related data role.
  • Transform complex data into accessible, reliable data models and insights.

Responsibilities

  • Transform complex data into accessible, reliable and performant data models and insights that drive organisational decision‑making.
  • Collaborate with stakeholders to understand analytical needs — partnering with Data Architects and Data Modellers to design scalable data models aligned with enterprise strategy.
  • Design and build efficient, reproducible data assets — including data models, data marts and semantic layers — with scalable transformations and pipelines for speed and consistency.
  • Apply CI/CD practices, testing frameworks and orchestration tools (e.g., Airflow) to productionise and maintain robust data solutions.
  • Embed data governance and quality assurance into every solution from the ground up.

Skills

Analytics engineering
Data modelling
Data governance
Software engineering principles

Education

Bachelor's Degree in Analytical/Data/Technical or Other

Tools

Airflow
Prefect

Job description

The Insights and Media Solutions team drives client data analytics and client optimisation strategies — made up of data and software engineering professionals alongside engagement strategy and operations specialists. Together, the team turns client data into meaningful, actionable intelligence that reaches millions of people. The Analytics Engineer sits at the heart of that — bridging the gap between data engineering and analytics, and building the data foundation that powers client engagement decisions.

Job description:

About the team

The Insights and Media Solutions team drives client data analytics and client optimisation strategies — made up of data and software engineering professionals alongside engagement strategy and operations specialists. Together, the team turns client data into meaningful, actionable intelligence that reaches millions of people. The Analytics Engineer sits at the heart of that — bridging the gap between data engineering and analytics, and building the data foundation that powers client engagement decisions.

Why this role exists

The Analytics Engineer II exists to bridge the gap between Data Engineers and Data Analysts — transforming complex data into accessible, reliable and performant data models and insights that drive decision-making across the organisation.This is not just a modelling role — it's an engineering role with an analytics lens. The team needs someone who can take complex, raw data and shape it into clean, trusted data assets that analysts and engineers can actually use, fast.

What you’ll do
  • Transform complex data into accessible, reliable and performant data models and insights that drive organisational decision-making
  • Collaborate with stakeholders to understand analytical needs — partnering with Data Architects and Data Modellers to design scalable data models aligned with enterprise strategy
  • Design and build efficient, reproducible data assets — including data models, data marts and semantic layers — along with scalable transformations and pipelines that empower Analytics Engineers and Data Analysts to deliver insights and reports with speed, consistency and minimal friction
  • Apply CI/CD practices, testing frameworks and orchestration tools (e.g., Airflow) to productionise and maintain robust data solutions
  • Embed data governance and quality assurance into every solution from the ground up
Minimum Experience
  • At least 5-8 years’ experience in analytics engineering or a closely related data role
  • Transform complex data into accessible, reliable and performant data models and insights that drive organisational decision-making
  • Collaborate with stakeholders to understand analytical needs — partnering with Data Architects and Data Modellers to design scalable data models aligned with enterprise strategy
  • Design and build efficient, reproducible data assets — including data models, data marts and semantic layers — along with scalable transformations and pipelines that empower Analytics Engineers and Data Analysts to deliver insights and reports with speed, consistency and minimal friction
  • Apply CI/CD practices, testing frameworks and orchestration tools (e.g., Airflow) to productionise and maintain robust data solutions
  • Embed data governance and quality assurance into every solution from the ground up
Qualifications (Minimum)
  • Bachelor's Degree in Analytical/Data/Technical or Other
Knowledge
  • Advanced grasp of:
  • Data modelling best practices.
  • Data governance and quality assurance.
  • Cloud data platforms and orchestration tools (e.g., Airflow, Prefect).
  • Understanding of software engineering principles (e.g., CI/CD, testing).
Conditions of Employment
  • Clear criminal and credit record

Profile description:

About the team

The Insights and Media Solutions team drives CRM, client data analytics and client optimisation strategies — made up of data and software engineering professionals alongside engagement strategy and operations specialists. Together, the team turns client data into meaningful, actionable intelligence that reaches millions of people. The Analytics Engineer sits at the heart of that — bridging the gap between data engineering and analytics, and building the data foundation that powers client engagement decisions.

Why this role exists

The Analytics Engineer II exists to bridge the gap between Data Engineers and Data Analysts — transforming complex data into accessible, reliable and performant data models and insights that drive decision-making across the organisation. This is not just a modelling role — it's an engineering role with an analytics lens. The team needs someone who can take complex, raw data and shape it into clean, trusted data assets that analysts and engineers can actually use, fast.

What you’ll do
  • Transform complex data into accessible, reliable and performant data models and insights that drive organisational decision-making
  • Collaborate with stakeholders to understand analytical needs — partnering with Data Architects and Data Modellers to design scalable data models aligned with enterprise strategy
  • Design and build efficient, reproducible data assets — including data models, data marts and semantic layers — along with scalable transformations and pipelines that empower Analytics Engineers and Data Analysts to deliver insights and reports with speed, consistency and minimal friction
  • Apply CI/CD practices, testing frameworks and orchestration tools (e.g., Airflow) to productionise and maintain robust data solutions
  • Embed data governance and quality assurance into every solution from the ground up
Minimum Experience
  • At least 5-8 years’ experience in analytics engineering or a closely related data role
  • Transform complex data into accessible, reliable and performant data models and insights that drive organisational decision-making
  • Collaborate with stakeholders to understand analytical needs — partnering with Data Architects and Data Modellers to design scalable data models aligned with enterprise strategy
  • Design and build efficient, reproducible data assets — including data models, data marts and semantic layers — along with scalable transformations and pipelines that empower Analytics Engineers and Data Analysts to deliver insights and reports with speed, consistency and minimal friction
  • Apply CI/CD practices, testing frameworks and orchestration tools (e.g., Airflow) to productionise and maintain robust data solutions
  • Embed data governance and quality assurance into every solution from the ground up
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