Job Description

Step into a high-impact Data Engineer role where you'll architect and run large-scale data pipelines across AWS and enterprise-grade data platforms. This is your chance to shape the data backbone powering analytics, operational systems, and business intelligence for a global automotive leader.
Own complex data ingestion, transformation, and provisioning streams-championing security, compliance, and data quality across enterprise-wide data assets. If you thrive in environments where data engineering meets strategy, this is your arena.
What makes this role stand out:
? Deep technical work with Python, PySpark, Terraform, AWS & Big Data frameworks
? Flexibility through a hybrid setup + 1960 annual flexible working hours
? Act as a technical mentor while owning key components of the enterprise data platform
You'll focus on delivering organisation-wide data products, spanning DGOs and Data Assets, handling secure data ingestion for priority Enterprise D&A use cases (TOP20), and enabling reliable data provisioning for critical operational processes.
POSITION: Contract: 01 February 2026 - 31 December 2028
EXPERIENCE: 8+ years related experience
COMMENCEMENT: 01 February 2026
LOCATION: Hybrid: Midrand/Menlyn/Rosslyn/Home Office rotation
TEAM: Data Science and Engineering - Enterprise Data & Analytics
The product focuses on creation and provisioning of enterprise-wide data spanning DGOs and Data Assets, including data protection and other compliance and security aspects. This includes data ingests for the Enterprise D&A Use Cases (TOP20) and data provisioning for operational processes.
Qualifications/Experience
Minimum mandatory qualifications:

• Relevant IT / Business / Engineering Degree

Certifications (Preferred): Candidates with one or more of the following certifications are preferred:

• AWS Certified Cloud Practitioner
• AWS Certified SysOps Associate
• AWS Certified Developer Associate
• AWS Certified Architect Associate
• AWS Certified Architect Professional
• HashiCorp Certified Terraform Associate

Minimum mandatory experience:

• Above average experience/understanding in data engineering and Big Data pipelines
• Experience in working with Enterprise Collaboration tools such as Confluence, JIRA
• Experience developing technical documentation and artefacts
• Knowledge of data formats such as Parquet, AVRO, JSON, XML, CSV
• Knowledge of the Agile Working Model

Essential Skills Requirements
Programming & Scripting:

• Python 3.x (above average experience)
• PySpark
• PowerShell / Bash
• Boto3

Infrastructure as Code:

• Terraform (above average experience)

Databases & Data Processing:

• SQL - Oracle/PostgreSQL (above average experience)
• ETL (above average experience)
• Big Data (above average experience)
• Technical data modelling and schema design ("not drag and drop")

AWS Cloud Services:

• Group Cloud Data Hub (CDH)
• Group CDEC Blueprint
• AWS Glue
• CloudWatch
• SNS (Simple Notification Service)
• Athena
• S3
• Kinesis Streams (Kinesis, Kinesis Firehose)
• Lambda
• DynamoDB
• Step Function
• Param Store
• Secrets Manager
• Code Build/Pipeline
• CloudFormation
• AWS EMR
• Redshift

Big Data Technologies:

• Kafka

Containerization & Operating Systems:

• Docker
• Linux / Unix

Analytics:

• Business Intelligence (BI) Experience

Soft Skills:

• Self-driven team player with ability to work independently and multi-task
• Strong written and verbal communication skills, with precise documentation
• Strong organizational skills
• Ability to work collaboratively in a team environment
• Problem-solving capabilities
• Above-board work ethics

Advantageous Skills Requirements

• Demonstrate expertise in data modelling Oracle SQL
• Exceptional analytical skills analysing large and complex data sets
• Perform thorough testing and data validation to ensure the accuracy of data transformations
• Strong written and verbal communication skills, with precise documentation
• Self-driven team player with ability to work independently and multi-task
• Experience building data pipeline using AWS Glue or Data Pipeline, or similar platforms
• Familiar with data store such as AWS S3, and AWS RDS or DynamoDB
• Experience and solid understanding of various software design patterns
• Experience preparing specifications from which programs will be written, designed, coded, tested and debugged
• Strong organizational skills
• Experience working with Data Quality Tools such as Great Expectations
• Experience developing and working with REST APIs
• Basic experience in Networking and troubleshooting network issues

Role Requirements
Data Pipeline Development:

• Build and maintain Big Data Pipelines using Group Data Platforms
• Design, develop, and optimize ETL processes for large-scale data ingestion and transformation
• Implement data pipelines using AWS Glue, Lambda, Step Functions, and other AWS services

Data Governance & Security:

• Act as custodian of data and ensure that data is shared in line with information classification requirements on a need-to-know basis
• Ensure data protection and compliance with security aspects
• Implement data quality checks and validation processes

Technical Leadership:

• Mentor, train and upskill members in the team
• Provide technical guidance on data architecture and best practices
• Review and approve technical designs and implementations

Innovation & Improvement:

• Stay up to date with the latest data engineering tools, technologies and industry trends
• Identify opportunities for process improvements and automation to enhance the efficiency and reliability of data pipelines
• Explore and evaluate new data engineering approaches and technologies to drive innovation within the organisation

Data Modelling & Architecture:

• Design and implement technical data models and schema designs
• Ensure scalability and performance of data solutions
• Create and maintain data architecture documentation

Collaboration:

• Work with cross-functional teams to gather requirements and deliver data solutions
• Collaborate with stakeholders to understand data needs and use cases
• Support Enterprise D&A Use Cases (TOP20) and operational processes

Testing & Quality Assurance:

• Perform thorough testing and data validation to ensure accuracy of data transformations
• Implement automated testing frameworks for data pipelines
• Monitor data pipeline performance and troubleshoot issues

Documentation:

• Develop technical documentation and artefacts
• Create and maintain runbooks and operational procedures
• Document data lineage and metadata

NB:
South African citizens / residents are preferred. Applicants with valid work permits will also be considered. By applying, you consent to be added to the database and to receive updates until you unsubscribe. If you do not receive a response within 2 weeks, please consider your application unsuccessful.
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Skills Required