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
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Design and build scalable, automated data pipelines using AWS Glue, Lambda, Kinesis, Step Functions, EMR
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Develop ETL/ELT processes for structured and unstructured data
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Enable real-time and batch data processing with focus on performance, reliability, and cost-efficiency
Cloud Data Architecture
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Work with AWS data services including S3, Redshift, Athena, RDS
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Implement Change Data Capture (CDC) for real-time data sync and streaming analytics
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Build and optimise data lakes, data warehouses, and AI/ML feature stores
AI/ML & Analytics Support
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Structure high-quality data for AI/ML model training and analytics reporting
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Collaborate with data scientists and analysts to deliver reliable, clean datasets
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Ensure seamless integration between data pipelines and analytics tools
DevOps & Automation
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Develop CI/CD pipelines for automated testing, deployment, and monitoring
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Use Infrastructure as Code tools (e.g., Terraform, CloudFormation) for scalable cloud setup
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Implement version control (Git/SVN), rollback strategies, and pipeline monitoring using CloudWatch
Continuous Improvement
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Regularly optimise pipelines to improve speed and lower costs
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Stay current with the latest in cloud data engineering trends and best practices
Requirements
Education & Experience
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Bachelor’s degree in Computer Science, Informatics, Engineering, Mathematics, or related field
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4–5 years of data engineering experience in cloud-based environments
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AWS certifications (e.g., Data Analytics or Solutions Architect) are a plus
Technical Skills
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Proficiency with:
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AWS Services: Redshift, Glue, Lambda, EMR, S3, Athena, IAM
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Programming Languages: Python, Java, Scala, C#
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Data processing tools: Apache Spark, Kafka, Kinesis
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ETL/ELT pipeline development
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DevOps practices including CI/CD and Infrastructure as Code (Terraform, CloudFormation)
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Version control (Git, SVN) and monitoring tools like AWS CloudWatch
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Key Attributes
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Analytical mindset – able to solve complex data problems
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Strong communicator – can explain data concepts to technical and non-technical teams
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Innovative thinker – always looking for smarter ways to improve data workflows
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Team player – works well across departments and in collaborative teams
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Adaptable – thrives in fast-changing environments and can juggle multiple tasks
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Committed to learning – actively stays updated on trends and new tools