Data Engineer: Build AI-Ready, Scalable Pipelines

Placements24; South Africa; On-site; ZAR 400,000 - 900,000; Full time

Job summary

LexisNexis Legal & Professional in Johannesburg invites a Data Engineer to design, build, and maintain reliable data pipelines and platforms supporting analytics and AI-ready data.

You will collaborate with technical and business partners, write high-quality SQL, model data, and ensure security and regulatory standards are met, including POPIA.

A degree in a related field and hands-on experience with ETL, data warehousing, and cloud services are expected to drive scalable data solutions.

Qualifications

• Bachelor's degree in computer science, data science, or a related field.
• Experience in data warehousing, ETL processes, and programming languages like Python or Java.
• Knowledge of cloud platforms and big data technologies.

Responsibilities

• Design, build, and maintain scalable data pipelines and integrations.
• Develop high-quality, well-tested code that follows best practices for readability, security, and maintainability.
• Use SQL as a primary tool to query, transform, validate, and optimize data across systems.
• Collaborate with technical and business partners to understand data needs and translate them into practical data solutions.
• Document data requirements and contribute to specifications for analytics and AI-enabled workflows.
• Troubleshoot and resolve data issues through root cause analysis and appropriate automation.

Skills

Python

Java

SQL

Data Warehousing

ETL

Data Modeling

Cloud Platforms

Tableau

Big Data

Education

Bachelor's degree

Tools

Tableau

Job description

LexisNexis Legal & Professional in Johannesburg invites a Data Engineer to design, build, and maintain reliable data pipelines and platforms supporting analytics and AI-ready data.

You will collaborate with technical and business partners, write high-quality SQL, model data, and ensure security and regulatory standards are met, including POPIA.

A degree in a related field and hands-on experience with ETL, data warehousing, and cloud services are expected to drive scalable data solutions.