Data Engineer (AI Focus)
Summary
A data engineer role in Rustenburg focused on building and maintaining scalable data pipelines, ETL/ELT processes, and data infrastructure that powers AI/ML systems. Core tech includes SQL/NoSQL databases, Spark/Hadoop, cloud platforms (AWS, Azure, GCP), Python or Scala, and orchestration tools like Airflow.
About the Role
Our client is looking for a skilled Data Engineer with a strong focus on AI initiatives to join their dynamic team in Rustenburg. This role is critical for building and optimizing the data infrastructure that powers our advanced AI and machine learning systems. You will be responsible for designing, constructing, installing, testing, and maintaining highly scalable data management systems. The ideal candidate possesses a passion for data quality, efficiency, and the ability to work with large, complex datasets to unlock valuable insights for AI applications, contributing to a data-driven culture within the organization.
Key Responsibilities
- Design, build, and maintain scalable data pipelines for AI and machine learning applications.
- Develop and manage ETL/ELT processes to ensure data quality and availability.
- Optimize data storage and retrieval systems for performance and cost-efficiency.
- Implement data governance and security best practices.
- Collaborate with data scientists and ML engineers to understand their data needs.
- Monitor data infrastructure and troubleshoot any issues that arise.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 3+ years of experience in data engineering, with exposure to AI/ML projects.
- Proficiency in SQL and NoSQL databases, data warehousing concepts, and data modeling.
- Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
- Programming skills in Python or Scala.
- Understanding of data pipeline orchestration tools (e.g., Airflow).
Benefits
- Competitive salary and performance-based incentives.
- Comprehensive health, dental, and vision insurance.
- Generous paid time off and holiday schedule.
- Opportunities for professional development and learning new technologies.
- A collaborative and innovative work environment focused on cutting-edge data solutions.