Data Engineer

Infinity Brands; Johannesburg; Hybrid; ZAR 600,000 - 800,000; Full time

Job summary

A leading data solutions provider in Johannesburg is seeking a hands-on Data Engineer to manage ELT pipelines and prepare BI datasets for executive reporting. The ideal candidate has strong SQL skills and 3-5 years of relevant experience in a hybrid Data Engineering and BI role. This position offers a hybrid work model and an opportunity to work with advanced tools like Mage and Zoho Analytics.

Benefits

Provident fund

Medical Aid

Hybrid working after probation

Qualifications

• 3-5 years experience in Data Engineering / BI hybrid roles.
• Strong SQL skills are required.
• Hands-on experience with ELT tools like Mage and Airbyte.

Responsibilities

• Maintain and enhance ELT pipelines.
• Prepare BI-ready datasets for reporting.
• Collaborate with automation engineers on data strategy.

Skills

SQL

Data Engineering

BI Enablement

Data Pipelines

Data Modeling

Education

Bachelor's degree in Computer Science or related field

Tools

Mage Postgres

Zoho Analytics

ELT tools

Job description

Overview

We are looking for a hands-on Data Engineer to take charge of our ELT pipelines, warehouse modeling, and BI-ready data layers. This role is a mix of 60% data engineering and 40% BI enablement with a strong emphasis on SQL data quality and performance-driven outputs.

You will be working with Mage Postgres and Zoho Analytics / DataPrep. If you have worked with tools like Hevo Stitch or Matillion, you will find the transition easy. Your work will directly power dashboards, KPIs, and executive decision-making for leading franchise brands.

Key Responsibilities

• Data Engineering (60%) — Maintain and enhance ELT pipelines on Mage (80% maintenance, 20% new connectors); design data models, schemas, and SQL view tables for BI and performance reporting; ensure data quality, accuracy, and consistency across the warehouse; troubleshoot and monitor data pipelines to keep the data flow smooth; document everything; reproducibility and handover are key.
• BI & Reporting Enablement (40%) — Prepare BI-ready datasets for Zoho Analytics dashboards; translate business OKRs into performance-driven datasets; support ad hoc SQL queries and reporting needs; build scalable data transformations that feed executive KPIs.
• Collaboration & Growth — Work with the CDAIO on strategy and architecture; partner with automation engineers on workflow and agentic processes; be part of future projects in ML and AI pipelines; stay ahead of open-source and emerging technologies.

Requirements

• 3-5 years experience in Data Engineering / BI hybrid roles.
• Strong SQL (must-have).
• Hands-on experience with ELT tools (Mage, Airbyte, Singer, etc.).
• Postgres or relational database experience.
• BI / reporting exposure (Zoho Analytics preferred; Power BI / Tableau / Qlik acceptable).
• Familiarity with APIs, JSON, and data integrations.
• Bonus Skills: Zoho DataPrep, scripting in Python, exposure to cloud warehouses (Snowflake, Redshift, BigQuery), ML pipeline curiosity.

Benefits

• Provident fund.
• Medical Aid.
• Hybrid after probation.

Employment & Qualifications

• Bachelor's degree in Computer Science, Information Technology, Business Administration, or related field.
• Proven experience (3 years) in IT project management, with a focus on software development or technology implementation projects.
• Strong proficiency in business analysis techniques, including requirements gathering, process modelling, and solution design.
• Excellent communication skills for nontechnical stakeholders; ability to manage multiple projects in a fast-paced environment.
• Project management certification (e.g., PMP, PRINCE2) and business analysis certification (e.g., CBAP, CCBA) advantageous.
• Experience with agile methodologies (e.g., Scrum, Kanban) and project management tools (e.g., ClickUp, Zoho Projects) is a plus; experience with SaaS and collaborative platforms (e.g., Zoho One, Google Workspace, Microsoft 365) is advantageous.

Key Skills

Apache Hive, S3, Hadoop, Redshift, Spark, AWS, Apache Pig, NoSQL, Big Data, Data Warehouse, Kafka, Scala