Senior AI/ML Data Engineer: Scalable Pipelines | Hybrid

Placements24; Sandton; Hybrid; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Salary bonuses

Hybrid work model

Health and retirement benefits

Professional development opportunities

Collaborative culture

Job summary

Placements24 in Sandton seeks a Senior Data Engineer focused on AI/ML data pipelines to design, build, and maintain scalable data infrastructure. You will work with data scientists to ensure clean, accessible data for model training and deployment in a hybrid work setting.

The ideal candidate has 5+ years in data engineering, strong SQL/NoSQL, and experience with Spark/Hadoop, cloud platforms, and data governance for AI contexts.

Qualifications

• 5+ years of data engineering experience building data infrastructure for AI/ML.
• Strong SQL and NoSQL, data warehousing, and big data tech (Spark, Hadoop).
• Experience with cloud platforms (AWS, Azure, GCP) and data pipelines orchestration.

Responsibilities

• Design, construct, install, test, and maintain scalable data pipelines for AI/ML applications.
• Develop and optimize data ingestion, transformation, and storage processes using big data technologies.
• Collaborate with data scientists and AI engineers to understand data requirements and provide robust data solutions.
• Ensure data quality, integrity, and security across all data platforms.
• Implement data governance and best practices for data management in an AI context.

Education

Bachelor's or Master's degree in Computer Science, Engineering, or related quantitative field

Tools

SQL

NoSQL

Data warehousing

Spark

Hadoop

Cloud platforms (AWS, Azure, GCP)

Data pipeline orchestration

Job description

Placements24 in Sandton seeks a Senior Data Engineer focused on AI/ML data pipelines to design, build, and maintain scalable data infrastructure. You will work with data scientists to ensure clean, accessible data for model training and deployment in a hybrid work setting.

The ideal candidate has 5+ years in data engineering, strong SQL/NoSQL, and experience with Spark/Hadoop, cloud platforms, and data governance for AI contexts.