AI Data Engineer
Summary
Build and maintain the data infrastructure behind a client's AI/ML initiatives in Port Elizabeth, South Africa (hybrid): designing scalable data pipelines and warehouses, developing ETL processes, and preparing large, high-quality datasets for machine learning models. Core stack includes SQL, Python/Pandas, Spark/Hadoop, and cloud big-data platforms.
About the Role
Our client is seeking a dedicated and skilled AI Data Engineer to contribute to their innovative projects in Port Elizabeth . This hybrid role offers a blend of on‑site collaboration and remote flexibility, focusing on building and maintaining the robust data infrastructure essential for AI and machine learning initiatives. You will be responsible for acquiring, cleaning, transforming, and preparing large datasets to fuel the development of sophisticated AI models. Join a growing team in Eastern Cape that values data integrity and efficiency, playing a key role in enabling data‑driven insights and AI advancements.
Key Responsibilities
- Design, construct, install, and maintain scalable data pipelines and data warehouses for AI/ML applications.
- Develop processes and tools for extracting, transforming, and loading (ETL) large datasets from various sources.
- Ensure data quality, accuracy, and availability for machine learning models and analytics.
- Optimize data retrieval performance and manage data storage solutions.
- Collaborate with data scientists and ML engineers to understand data requirements and delivery needs.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
- Proven experience as a Data Engineer, with a focus on big data technologies and cloud platforms.
- Proficiency in SQL, Python, and data manipulation libraries (e.g., Pandas).
- Experience with distributed data processing frameworks like Spark or Hadoop.
- Familiarity with data warehousing concepts and building data pipelines for ML use cases.
Benefits
- Competitive salary commensurate with experience.
- Hybrid work arrangement balancing office and remote work.
- Comprehensive health and wellness benefits.
- Access to modern data infrastructure and tools.
- Contribute to impactful AI projects in a supportive team environment.