Senior AI Data Engineer: Python, SQL Pipelines (Hybrid)

Network Finance; South Africa; Hybrid; ZAR 900,000 - 1,200,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Network Finance is seeking a Senior AI Data Engineer to join their expanding data science team in Sandton, Gauteng. You will design, build, and maintain data infrastructure for advanced AI/ML applications, ensuring data quality and optimized pipelines to support data scientists and ML engineers.

The role involves working with large datasets, implementing data governance, and collaborating with stakeholders to translate business questions into data-driven solutions.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 5+ years of experience in data engineering, with a focus on supporting AI/ML workloads.
• Strong proficiency in SQL, Python, and data processing frameworks (e.g., Spark, Hadoop).
• Experience with cloud data services (AWS Redshift, Azure Data Lake, Google BigQuery).
• Solid understanding of ETL/ELT processes and data modeling techniques.

Responsibilities

• Design, develop, and optimize scalable data pipelines for AI and machine learning projects.
• Implement and manage data warehousing solutions and data lakes, ensuring data integrity and accessibility.
• Collaborate with data scientists and ML engineers to understand data requirements and deliver robust data solutions.
• Develop and maintain data governance policies and ensure compliance with data privacy regulations.
• Monitor data infrastructure performance, troubleshoot issues, and implement improvements for efficiency and reliability.

Skills

Python

SQL

Pandas

NumPy

Data analysis

Problem solving

Education

Bachelor's or Master's degree

Tools

Spark

Hadoop

AWS Redshift

Azure Data Lake

Google BigQuery

Job description

Network Finance is seeking a Senior AI Data Engineer to join their expanding data science team in Sandton, Gauteng. You will design, build, and maintain data infrastructure for advanced AI/ML applications, ensuring data quality and optimized pipelines to support data scientists and ML engineers.

The role involves working with large datasets, implementing data governance, and collaborating with stakeholders to translate business questions into data-driven solutions.