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Junior Analytics Engineer

Cape Town, South Africa

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Apply at Pargo

What you’ll work on

Full posting

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.

  • You will work closely with the Data Team Lead and partner across Commercial, Operations, and Engineering teams.

From the employer’s posting
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.
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

What you’ll bring

All qualifications

Core 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)..
  • Familiarity with a Postgres-based or cloud data warehouse environment.
  • Experience working in a scale-up or fast-paced operational environment.
  • Bachelor’s degree in Engineering, Computer Science, Data Science, Information Systems, or a closely related quantitative field.
  • Solid understanding of core data modeling concepts and best practices.
Qualification wording
0 - 2 years of experience in a data-centric role, or a strong portfolio of projects demonstrating your data skills (open to ambitious graduates)..
Familiarity with a Postgres-based or cloud data warehouse environment.
Experience working in a scale-up or fast-paced operational environment.
Bachelor’s degree in Engineering, Computer Science, Data Science, Information Systems, or a closely related quantitative field.
Solid understanding of core data modeling concepts and best practices.

Tools in this posting

  • SQL
  • dbt
  • Python
  • PostgreSQL
  • Power BI
  • Tableau
Source — Tool mentions in context
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).
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.
- 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.
- Basic knowledge of Git for version control and collaborative workflows. - Knowledge of Python. Nice to have
- 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.
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.

Benefits in the posting

Full benefits wording
  • Why join PARGO
  • Contribution to medical aid and group life cover.

From the employer’s posting.

About Pargo

Pargo is transforming last-mile delivery in South Africa through smarter, more accessible logistics solutions.

In the employer’s words · Read in context

Job description

View original posting ↗


About the role

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



Benefits

Why join PARGO

  • 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.



Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on pargo.zohorecruit.com. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

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Pay

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Location & working pattern

Cape Town, South Africa

- Contribution to medical aid and group life cover. - Flexible working hours and hybrid setup. - Strong focus on personal growth and skill development.
Work authorization

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Status in our records
Active
First seen by us
Jul 15, 2026
Recorded sightings
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Last seen by us
Oct 6, 2026

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