AI Data Engineer - Hybrid Role Building AI Pipelines

Placements24; Noord-Kaap; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Hybrid work model

Health insurance

Professional development

Job summary

Placements24 is seeking an AI Data Engineer in Kimberley to design, build, and optimize data pipelines for AI/ML initiatives. You will ensure data availability, quality, and accessibility for model training in a data-centric team.

The role involves collaborating with data scientists and ML engineers, implementing governance, and maintaining scalable data infrastructure in a hybrid work setting. A strong background in SQL, Spark/Hadoop, and cloud data services is essential.

Qualifications

• Bachelor's degree in CS, Engineering or related field.
• 3+ years of data engineering experience supporting AI/ML projects.
• Proficiency in SQL and experience with relational and NoSQL databases.
• Experience with big data technologies such as Apache Spark, Hadoop, or similar.
• Familiarity with cloud data services (AWS Glue, Azure Data Factory, GCP Dataflow).
• Programming skills in Python or Scala for data manipulation and pipeline development.

Responsibilities

• Design, build, and maintain scalable and efficient data pipelines for AI/ML applications.
• Develop ETL/ELT processes to ingest, transform, and prepare data from various sources.
• Ensure data quality, integrity, and consistency across all data systems.
• Optimize data storage and query performance for large-scale datasets.
• Collaborate with data scientists and ML engineers to understand data requirements and provide necessary datasets.
• Implement data governance and security best practices.

Skills

SQL

Relational databases

NoSQL databases

Big data (Spark/Hadoop)

Cloud data services

Python

Scala

Education

Bachelor's degree in CS/Engineering

Tools

Apache Hadoop

Apache Spark

AWS Glue

Azure Data Factory

GCP Dataflow

Job description

Placements24 is seeking an AI Data Engineer in Kimberley to design, build, and optimize data pipelines for AI/ML initiatives. You will ensure data availability, quality, and accessibility for model training in a data-centric team.

The role involves collaborating with data scientists and ML engineers, implementing governance, and maintaining scalable data infrastructure in a hybrid work setting. A strong background in SQL, Spark/Hadoop, and cloud data services is essential.