AI Data Engineer

Placements24; East London; Híbrido; ZAR 600.000 - 1.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Health insurance

Paid time off

Professional development

Retirement savings plan

Team social events

Descripción de la vacante

Placements24 is seeking an AI Data Engineer in East London to design and optimize data pipelines and infrastructure for AI/ML initiatives. You will ensure data quality and efficiency for data science teams, working with cloud platforms and modern big data technologies in a collaborative environment.

The role emphasizes building robust data architectures, implementing governance and security, and staying current with emerging data engineering practices to support AI deployments.

Formación

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.

Responsabilidades

• Design, build, and maintain scalable and robust data pipelines for AI and machine learning applications.
• Implement ETL/ELT processes to ingest, transform, and load data from various sources into data warehouses or data lakes.
• Ensure data quality, integrity, and consistency across all data platforms.
• Optimize data architectures and query performance for large-scale datasets.
• Collaborate with data scientists and ML engineers to understand their data needs and provide efficient data solutions.
• Develop and manage data infrastructure on cloud platforms (e.g., AWS, Azure, GCP).
• Implement data governance, security, and compliance measures.
• Automate data-related processes and workflows.
• Monitor data pipeline performance and troubleshoot any issues.
• Stay current with emerging big data technologies and data engineering best practices.

Descripción del empleo

About the Role

Our client, a rapidly growing data analytics firm, is seeking a proficient AI Data Engineer to join their dedicated team in East London, Eastern Cape . This role is integral to our AI initiatives, focusing on building and optimizing the data pipelines and infrastructure necessary for machine learning model development and deployment. You will work with vast datasets, ensuring data quality, accessibility, and efficiency for our data science teams. The ideal candidate has a strong background in data engineering, big data technologies, and a solid understanding of the data requirements for AI/ML projects. This is an excellent opportunity to contribute to the core data foundations of our AI solutions in a dynamic and collaborative environment.

We pride ourselves on fostering an inclusive and diverse workplace.

Key Responsibilities

• Design, build, and maintain scalable and robust data pipelines for AI and machine learning applications.
• Implement ETL/ELT processes to ingest, transform, and load data from various sources into data warehouses or data lakes.
• Ensure data quality, integrity, and consistency across all data platforms.
• Optimize data architectures and query performance for large-scale datasets.
• Collaborate with data scientists and ML engineers to understand their data needs and provide efficient data solutions.
• Develop and manage data infrastructure on cloud platforms (e.g., AWS, Azure, GCP).
• Implement data governance, security, and compliance measures.
• Automate data-related processes and workflows.
• Monitor data pipeline performance and troubleshoot any issues.
• Stay current with emerging big data technologies and data engineering best practices.

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
• Proven experience as a Data Engineer, with a strong focus on building data pipelines for AI/ML projects.
• Proficiency in SQL and experience with database systems (relational and NoSQL).
• Experience with big data technologies such as Spark, Hadoop, or Kafka.
• Strong programming skills in Python or Scala.
• Familiarity with cloud data services on platforms like AWS (e.g., S3, Redshift, Glue), Azure (e.g., Data Lake Storage, Synapse Analytics), or GCP (e.g., BigQuery, Cloud Storage).
• Understanding of data warehousing concepts and data modeling techniques.
• Knowledge of data governance and data security principles.
• Experience with containerization technologies (e.g., Docker) is a plus.
• Excellent problem-solving, analytical, and communication skills.

Benefits

• Competitive salary and performance incentives.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and sick leave policies.
• Opportunities for professional growth and skill development.
• Exposure to cutting-edge AI and data technologies.
• Supportive team environment fostering collaboration.
• Retirement savings plan with company contributions.
• Employee assistance program for personal well-being.
• Hybrid work model offering flexibility.
• Regular team social events and company gatherings.