Job Description

Position: Data Engineer (x2)
Listing Reference: woolw_001258
Location: Cape Town, South Africa
Contract Type: Permanent
Industry: FMCG, Retail, Wholesale, and Supply Chain
Application Deadline: 3 July 2025
Remuneration: Market Related

Join a fast-paced retail technology team as a Data Engineer, where you’ll help design and build large-scale, cloud-based data solutions. You’ll develop automated pipelines, manage real-time and batch data processing, and support advanced analytics and AI/ML initiatives in a highly collaborative environment.

The Role

As a Data Engineer, you will:

Data Pipeline Development

• Design and build scalable, automated data pipelines using AWS Glue, Lambda, Kinesis, Step Functions, EMR

• Develop ETL/ELT processes for structured and unstructured data

• Enable real-time and batch data processing with focus on performance, reliability, and cost-efficiency

Cloud Data Architecture

• Work with AWS data services including S3, Redshift, Athena, RDS

• Implement Change Data Capture (CDC) for real-time data sync and streaming analytics

• Build and optimise data lakes, data warehouses, and AI/ML feature stores

AI/ML & Analytics Support

• Structure high-quality data for AI/ML model training and analytics reporting

• Collaborate with data scientists and analysts to deliver reliable, clean datasets

• Ensure seamless integration between data pipelines and analytics tools

DevOps & Automation

• Develop CI/CD pipelines for automated testing, deployment, and monitoring

• Use Infrastructure as Code tools (e.g., Terraform, CloudFormation) for scalable cloud setup

• Implement version control (Git/SVN), rollback strategies, and pipeline monitoring using CloudWatch

Continuous Improvement

• Regularly optimise pipelines to improve speed and lower costs

• Stay current with the latest in cloud data engineering trends and best practices

Requirements

Education & Experience

• Bachelor’s degree in Computer Science, Informatics, Engineering, Mathematics, or related field

• 4–5 years of data engineering experience in cloud-based environments

• AWS certifications (e.g., Data Analytics or Solutions Architect) are a plus

Technical Skills

• Proficiency with:

  • AWS Services: Redshift, Glue, Lambda, EMR, S3, Athena, IAM

  • Programming Languages: Python, Java, Scala, C#

  • Data processing tools: Apache Spark, Kafka, Kinesis

  • ETL/ELT pipeline development

  • DevOps practices including CI/CD and Infrastructure as Code (Terraform, CloudFormation)

  • Version control (Git, SVN) and monitoring tools like AWS CloudWatch

Key Attributes

• Analytical mindset – able to solve complex data problems

• Strong communicator – can explain data concepts to technical and non-technical teams

• Innovative thinker – always looking for smarter ways to improve data workflows

• Team player – works well across departments and in collaborative teams

• Adaptable – thrives in fast-changing environments and can juggle multiple tasks

• Committed to learning – actively stays updated on trends and new tools