Senior Gtm Analytics Engineer — Remote & Equity

Carbon Data Solutions; South Africa; Remote; ZAR 600,000 - 1,200,000; Full time

Benefits offered by this job

Remote work

Professional development

Modern data infrastructure

Competitive salary

AI-driven environment

Job summary

Carbon Data Solutions seeks a Remote AI Data Engineer to design and maintain scalable data pipelines for AI/ML initiatives. You will gather, clean, and transform large datasets, enabling model training and analytics in a fully remote setup.

Ideal candidates have a background in data engineering with Python/SQL/Scala, experience with Spark or Hadoop, and familiarity with AWS, Azure, or GCP. A strong data warehousing foundation is required.

Qualifications

• Bachelor's degree or higher in a related field.
• 3+ years of data engineering experience with AI/ML data prep.
• Proficiency in Python, SQL, or Scala.
• Experience with Spark, Hadoop or Kafka.
• Familiarity with cloud data platforms (AWS/Azure/GCP).
• Strong data warehousing concepts and DB tech.

Responsibilities

• Design, build, and maintain scalable data pipelines for AI/ML apps.
• Develop ETL/ELT processes to ingest/transform data.
• Optimize storage and retrieval for large datasets.
• Collaborate with data scientists to meet data needs.
• Implement data governance and quality assurance measures.
• Monitor systems and troubleshoot data availability and integrity.

Skills

Data engineering

AI/ML data preparation

Python

SQL

Scala

Big data concepts

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Spark

Hadoop

Kafka

AWS

Azure

GCP

Job description

Our client is seeking a highly skilled Remote AI Data Engineer to construct and maintain robust data pipelines essential for our artificial intelligence and machine learning initiatives. In this fully remote position, you will be responsible for collecting, processing, and transforming vast amounts of data to make it ready for analysis and model training. You will work with cutting‑edge big data technologies and cloud platforms to ensure data quality, accessibility, and efficiency. This role is critical for enabling our data science teams to build and deploy effective AI solutions, making it a key position within our technology organization.

About the Role

Our client is seeking a highly skilled Remote AI Data Engineer to construct and maintain robust data pipelines essential for our artificial intelligence and machine learning initiatives. In this fully remote position, you will be responsible for collecting, processing, and transforming vast amounts of data to make it ready for analysis and model training. You will work with cutting‑edge big data technologies and cloud platforms to ensure data quality, accessibility, and efficiency. This role is critical for enabling our data science teams to build and deploy effective AI solutions, making it a key position within our technology organization.

Key Responsibilities

• Design, build, and maintain scalable and reliable data pipelines for AI/ML applications.
• Develop ETL/ELT processes to ingest, clean, and transform data from various sources.
• Optimize data storage and retrieval processes for large‑scale datasets.
• Collaborate with data scientists and AI engineers to understand their data requirements.
• Implement data governance and quality assurance measures.
• Monitor data systems and troubleshoot issues to ensure data availability and integrity.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
• 3+ years of experience in data engineering or a similar role, with a focus on AI/ML data preparation.
• Proficiency in programming languages such as Python, SQL, or Scala.
• Experience with big data technologies (e.g., Spark, Hadoop, Kafka).
• Familiarity with cloud data platforms (AWS, Azure, GCP) and their data services.
• Strong understanding of data warehousing concepts and database technologies.

Benefits

• Competitive salary and benefits package.
• Fully remote work opportunity, offering flexibility and work‑life balance.
• Access to modern data infrastructure and tools.
• Opportunities for continuous learning and professional development in data engineering and AI.
• Be part of a forward‑thinking company driving innovation with AI.