Overview
Data Engineer (Artificial Intelligence) Jobs in Johannesburg Metropolitan Area at Indsafri
Title: Data Engineer (Artificial Intelligence)
Company: Indsafri
Location: Johannesburg Metropolitan Area
Description:
We are seeking a highly skilled and motivated Data Engineer with a focus on Artificial Intelligence (AI) to join our dynamic team. The ideal candidate will be responsible for designing, building, and maintaining robust data pipelines and infrastructure that support our AI and machine learning initiatives. You will work closely with data scientists, ML engineers, and other stakeholders to ensure data quality, accessibility, and efficiency for AI model development and deployment.
Key Responsibilities:
- Design, develop, and optimize scalable data pipelines for ingesting, transforming, and storing large volumes of data for AI/ML applications.
- Build and maintain data infrastructure, including data warehouses, data lakes, and real-time data processing systems.
- Implement data governance best practices to ensure data accuracy, consistency, and security.
- Collaborate with data scientists and ML engineers to understand their data requirements and provide them with clean, well-structured datasets.
- Develop and implement monitoring and alerting systems for data pipelines and infrastructure.
- Optimize data processing for performance and cost-efficiency.
- Stay up-to-date with the latest trends and technologies in data engineering, AI, and machine learning.
- Troubleshoot and resolve data-related issues in production environments.
Required Skills and Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Proven experience as a Data Engineer or in a similar role.
- Strong proficiency in SQL and experience with relational and NoSQL databases.
- Expertise in at least one major programming language such as Python, Java, or Scala.
- Experience with big data technologies like Spark, Hadoop, Kafka, or Flink.
- Hands-on experience with cloud platforms (AWS, Azure, GCP) and their data services.
- Familiarity with data warehousing concepts and ETL/ELT processes.
- Understanding of machine learning concepts and the data requirements for AI models.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
Preferred Qualifications:
- Experience with MLOps principles and tools.
- Familiarity with containerization technologies like Docker and Kubernetes.
- Experience with data modeling and schema design.
- Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Work