Junior Analytics Engineer

Pargo; Cape Town; Hybrid; ZAR 300,000 - 420,000; Full time

Benefits offered by this job

Competitive remuneration

Medical aid & group life cover

Flexible hours & hybrid setup

Personal growth & development

Office in Gardens, Cape Town

Job summary

Pargo is seeking an Analytics Engineer to own the transformation and modeling layer of our data platform in Cape Town. You will build analytics-ready datasets that power reporting and strategic insight.

You will focus on durable data models with dbt, data quality, and collaboration with Commercial, Operations, and Engineering teams, while maintaining documentation and version control.

Qualifications

• Bachelor's degree in Engineering, Computer Science, Data Science, Information Systems, or a closely related quantitative field.
• Strong foundation in analytical problem-solving and systems thinking is expected.

Responsibilities

• Build, maintain, and optimize analytics-ready data models using dbt.
• Own transformation logic across core datasets, ensuring correctness, performance, and scalability.
• Implement and maintain data quality tests, freshness checks, and validation rules.
• Partner with stakeholders to translate business questions into reusable, scalable data models.
• Maintain clear and accurate documentation for data models, metrics, and business logic.
• Review and manage changes using Git-based version control.
• Support downstream analytics and reporting teams by ensuring data reliability and clarity.
• Continuously improve existing models and pipelines rather than rebuilding unnecessarily.

Skills

SQL

dbt

PostgreSQL

Git

Python

Data modeling

Education

Bachelor's degree in Engineering/CS/Data Science/IS

Tools

dbt

Git

PostgreSQL

Job description

Cape Town, South Africa | Posted on 14/07/2026

At Pargo, data is a core enabler of how we scale, operate, and serve customers.

As an Analytics Engineer, you will own the transformation and modeling layer of our data platform. Your work ensures that raw data is converted into reliable, well-structured, analytics-ready datasets that power reporting, operational decision-making, and strategic insight.

You will focus on building durable data models, maintaining data quality, and enabling analysts and stakeholders to work with trusted data. You will work closely with the Data Team Lead and partner across Commercial, Operations, and Engineering teams.

What you will be responsible for

Build, maintain, and optimize analytics-ready data models using dbt.

Own transformation logic across core datasets, ensuring correctness, performance, and scalability.

Implement and maintain data quality tests, freshness checks, and validation rules.

Partner with stakeholders to translate business questions into reusable, scalable data models.

Maintain clear and accurate documentation for data models, metrics, and business logic.

Review and manage changes using Git-based version control.

Support downstream analytics and reporting teams by ensuring data reliability and clarity.

Continuously improve existing models and pipelines rather than rebuilding unnecessarily.

Requirements

What we're looking for

Experience

0 - 2 years of experience in a data-centric role, or a strong portfolio of projects demonstrating your data skills (open to ambitious graduates)..

Exposure to or a strong conceptual understanding of data models and data transformation (experience with personal or academic projects is highly valued).

Core technical skills

Foundational to intermediate SQL with an understanding of how to model datasets.

Exposure to or hands-on experience using dbt (experience through personal projects, bootcamps, or university work is welcome).

Familiarity with a Postgres-based or cloud data warehouse environment.

Solid understanding of core data modeling concepts and best practices.

Basic knowledge of Git for version control and collaborative workflows.

Knowledge of Python.

Nice to have

Exposure to BI tools such as Zoho Analytics, Power BI, or Tableau.

Experience working in a scale-up or fast-paced operational environment.

Qualifications

Bachelor's degree in Engineering, Computer Science, Data Science, Information Systems, or a closely related quantitative field.

A strong foundation in analytical problem-solving and systems thinking is expected

Work on real, high-impact data problems in logistics and e-commerce.

Influence how data is modeled and used across the business.

Learn from experienced, hands-on leaders in a scale-up environment.

• Competitive remuneration.
• Contribution to medical aid and group life cover.
• Flexible working hours and hybrid setup.
• Strong focus on personal growth and skill development.
• A collaborative team culture and a great office in Gardens, Cape Town.

About PARGO

Pargo is transforming last-mile delivery in South Africa through smarter, more accessible logistics solutions. Our growing network of Pick-Up Points enables businesses and consumers to move parcels efficiently, even in areas traditional delivery struggles to reach. We are a technology-driven company focused on execution, innovation, and measurable impact.