Data Engineer

Araxi Group; Gauteng; On-site; ZAR 900,000 - 1,200,000; Full time

Benefits offered by this job

Competitive salary

Learning opportunities

Job summary

Araxi Group in Gauteng, South Africa, is seeking a Data Engineer to design, build, and optimise scalable data pipelines and analytics platforms, enabling business insights from batch and real-time data.

The role collaborates with an agile team, using AWS, PySpark, Spark, Hadoop, and Talend to develop secure, reliable data infrastructures and CI/CD for data platforms.

Qualifications

• 5+ years experience in Data or Software Engineering.
• 2+ years with Big Data technologies and platforms.
• 2+ years ETL with tooling and Python data processing.
• 2+ years AWS cloud experience (EMR, EC2, S3).
• Strong data modelling and scalable architecture knowledge.

Responsibilities

• Design, build, and maintain scalable data analytics frameworks and data platforms.
• Translate requirements into scalable architecture and high-performing data solutions.
• Develop batch and real-time data processing using modern big data tech.
• Create secure data pipelines between on-prem and AWS cloud environments.
• Develop ETL processes and data transformation workflows using Talend or similar tools.
• Manipulate, process, and analyse data using Python and related tech.
• Support Big Data and BI solutions with automated testing and deployment.
• Process large-scale datasets using Hadoop paradigms and AWS EMR services.
• Contribute to database development, optimisation, and operational management.
• Participate in software development, DevOps, and data operations.
• Ensure alignment with policies, standards, DR, and BC practices.

Skills

Data engineering

Python development

AWS cloud

Spark/Hadoop

ETL development

Education

Bachelor's degree

AWS certification advantageous

Tools

Talend

PySpark

AWS EMR

S3

Hadoop

Job description

The Data Engineer is responsible for building, supporting, and optimising scalable, repeatable, and secure data pipelines and analytical platforms. Operating as a core member of an agile engineering team, the role focuses on enabling business insights through the integration, transformation, and management of large-scale batch and real-time data solutions. The Data Engineer works across cloud and big data technologies to architect, develop, and support modern data platforms that enable analytics, reporting, automation, and data-driven decision-making.

Key Responsibilities

• Design, build, and maintain scalable data analytics frameworks and data platforms.
• Translate complex functional and technical requirements into scalable architecture and high-performing data solutions.
• Develop and support batch and real-time data processing solutions using modern big data technologies.
• Create and maintain secure and reliable data pipelines between on-premise systems and AWS cloud environments.
• Develop and maintain ETL processes and data transformation workflows using Talend or similar ETL tools.
• Manipulate, process, and analyse data using Python and related technologies.
• Develop and support Big Data and Business Intelligence solutions including automated testing and deployment practices.
• Process large-scale datasets using Hadoop paradigms and AWS EMR services.
• Support production data feeds and resolve operational issues through break-fix support activities.
• Contribute to database development, optimisation, and operational management.
• Participate in software development, DevOps, and data operations activities.
• Ensure alignment with policies, standards, procedures, business continuity, and disaster recovery practices.
• Research and evaluate emerging technologies, tools, and frameworks relevant to data engineering and analytics.
• Collaborate with business and technical stakeholders to understand data requirements and deliver effective solutions.

Essential Skills & Experience

• 5+ years’ experience in Data Engineering or Software Engineering roles.
• 2+ years’ experience working with Big Data technologies and platforms.
• 2+ years’ experience with ETL processes and tooling.
• 2+ years’ experience working with AWS cloud technologies.
• Strong experience with Python for data manipulation and processing.
• Hands-on experience with AWS services including EMR, EC2, and S3.
• Experience with PySpark, Spark, Hadoop, or distributed data processing frameworks.
• Strong understanding of data modelling, data structures, and scalable data architecture design.
• Experience designing highly scalable distributed systems using open-source technologies.
• Strong understanding of object-oriented design, coding standards, and testing practices.
• Experience working with large-scale data infrastructure and analytical platforms.
• Strong analytical, troubleshooting, and problem-solving skills.

Desirable Skills & Experience

• Experience with real-time streaming and event-driven data processing.
• Exposure to cloud-native data engineering architectures.
• Experience implementing automated deployment and CI/CD practices for data platforms.
• Exposure to business intelligence and analytics tooling.
• Experience working within agile software delivery environments.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Information Technology, or equivalent practical experience.
• AWS certification would be advantageous.

Behavioural Competencies

• Strong analytical and problem-solving mindset.
• Excellent communication and stakeholder engagement skills.
• Strong attention to detail and commitment to quality.
• Ability to work effectively both independently and within collaborative agile teams.
• Adaptability and willingness to learn evolving technologies and tools.
• Proactive mindset with focus on innovation and continuous improvement.

What We Offer

• Competitive salary and benefits package.
• Opportunity to work on modern cloud and big data platforms.
• Exposure to large-scale data engineering and analytics projects.
• Collaborative and innovative engineering environment.
• Professional growth and learning opportunities.
• Opportunity to contribute to impactful data-driven solutions.