Senior AI Data Engineer - Hybrid Pipelines for ML

Placements24; Sandton; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Hybrid work model

Competitive salary

Professional development

Dynamic Sandton team

Job summary

Placements24 in Sandton seeks a Senior AI Data Engineer to design, build, and maintain data infrastructure supporting AI and ML workloads. You will work closely with data scientists and ML engineers to deliver robust data solutions and ensure data quality across large datasets.

The role emphasizes data warehousing and data lake development, governance, and compliance, with a hybrid work model and a focus on reliability and optimization.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field.
• 5+ years of experience in data engineering, with a focus on AI/ML workloads.
• Strong proficiency in SQL, Python, and data processing frameworks (Spark, Hadoop).
• Experience with cloud data services (AWS Redshift, Azure Data Lake, Google BigQuery).
• Solid understanding of ETL/ELT processes and data modeling techniques.

Responsibilities

• Design, develop, and optimize scalable data pipelines for AI/ML projects.
• Implement and manage data warehousing solutions and data lakes, ensuring data integrity and accessibility.
• Collaborate with data scientists and ML engineers to understand data requirements and deliver robust data solutions.
• Develop and maintain data governance policies and ensure compliance with data privacy regulations.
• Monitor data infrastructure performance, troubleshoot issues, and implement improvements for efficiency and reliability.

Skills

SQL

Python

Data modeling

Education

Bachelor’s or Master’s degree in Computer Science/Engineering

Tools

Spark

Hadoop

AWS Redshift

Azure Data Lake

Google BigQuery

Job description

Placements24 in Sandton seeks a Senior AI Data Engineer to design, build, and maintain data infrastructure supporting AI and ML workloads. You will work closely with data scientists and ML engineers to deliver robust data solutions and ensure data quality across large datasets.

The role emphasizes data warehousing and data lake development, governance, and compliance, with a hybrid work model and a focus on reliability and optimization.