MagicOrange is a globally recognized leader in the IT Financial Management Software market, as acknowledged by Gartner. With customers and a strong presence on four continents, we are a Software as a Service (SaaS) provider in a high-growth phase. Our mission is to empower individuals and organizations, enhancing their value through our innovative software solutions.
Location: Mount Edgecombe, Durban or Sandton, Gauteng
Position Summary
We are seeking an experienced Data Engineer to design, build, and optimise scalable data platforms that power MagicOrange’s AI-driven cost intelligence products. You will play a critical role in shaping our modern data architecture, enabling reliable analytics, advanced reporting, and AI experimentation at scale.
Working closely with product, engineering, DevOps, and data science teams, you will ensure that data is trusted, performant, and readily available to support both internal decision-making and customer-facing features.
Key Responsibilities
Data Platform & Pipeline Engineering
- Design, develop, and maintain robust ETL / ELT pipelines across cloud-based data platforms.
- Build and optimise data lakes and lakehouse architectures (Medallion approach) using Azure and Databricks.
- Develop scalable, reusable, and metadata-driven data processing frameworks.
- Ensure data pipelines are reliable, maintainable, and production-ready across dev, test, and production environments.
Data Modelling & Performance Optimisation
- Design and implement dimensional and analytical data models to support reporting, analytics, and AI use cases.
- Optimise data processing and query performance across large-scale datasets.
- Implement indexing, partitioning, and distribution strategies to ensure high-performance data access.
- Continuously monitor and improve data platform efficiency and cost usage.
Data Quality, Governance & Reliability
- Implement best practices for data quality, validation, and observability.
- Support data governance initiatives, including metadata management, lineage, and data compliance.
- Ensure data platforms align with security, privacy, and regulatory requirements (including GDPR).
- Collaborate with DevOps and security teams to ensure secure and compliant data environments.
Collaboration & AI Enablement
- Work closely with data science and AI teams to enable model training, deployment, and experimentation.
- Support Databricks-based analytics, streaming, and AI workloads.
- Translate business and product requirements into scalable data solutions.
- Provide technical guidance and mentorship to other data engineers.
Soft Skills
- Strong communication skills, with the ability to explain complex data concepts to both technical and non-technical stakeholders.
- A collaborative mindset, comfortable working across product, engineering, DevOps, and data science teams.
- Proactive and solution-oriented, able to identify issues early and drive them through to resolution.
- Comfortable operating in a fast-paced, high-growth SaaS environment where priorities evolve.
- Demonstrates ownership and accountability for data platforms, quality, and outcomes.
- A natural mentor who enjoys sharing knowledge and raising the technical bar of the team.
Experience requirements
- 8+ years of professional experience in data engineering or data warehousing, with demonstrated operation at senior or lead level in production environments.
- Proven experience designing, building, and owning end-to-end data platforms (ETL / ELT, data lakes or lakehouse architectures) in the cloud, preferably Microsoft Azure.
- Strong hands-on experience with SQL and modern data processing frameworks (e.g. Databricks, Spark, PySpark) to deliver scalable, high-performance data solutions.
- Demonstrated ability to make architecture, performance, and cost optimisation decisions, while collaborating closely with engineering, DevOps, and data science teams.
Qualifications
- Matric (Grade 12 or equivalent)
- Relevant Bachelor’s degree or Diploma in a related field such as:
- Computer Science
- Information Systems
- Data Science / Business Analytics
- Engineering or similar technical discipline
- Relevant professional certifications in cloud platforms or data engineering (e.g. Azure, Databricks) are advantageous
What We Offer
- A strong entrepreneurial spirit, with the ability to make a real impact and see the results of your efforts
- Ongoing training and exposure to the latest cloud, data, and AI technologies
- The opportunity to work in a high-growth industry on a globally recognised SaaS product
- A challenging and rewarding career in an innovative, forward-thinking company
- The ability to influence outcomes, working in an open, collaborative environment close to decision-makers
- A competitive remuneration package, including flexible pension options
Join us at MagicOrange and help shape the future of IT Financial Management and FinOps software, ensuring our customers achieve the highest levels of value, insight, and success.
MagicOrange is an equal opportunity employer, committed to promoting diversity and inclusion in the workplace. We value and appreciate the diverse contributions and perspectives of all our employees.
Top Skills
What We Do
MagicOrange is a cloud-native, enterprise IT Financial Management solution, incorporating an intuitive cost allocation platform to correlate and assign IT, shared services and direct divisional spend to business activities at scale
- Optimisation: Actionable insights inform investment and prioritisation decisions to improve utilisation, performance and profitability
- Alignment: Understand the business value of IT and drive accountability and ownership in the business
- Efficiency: Materially improve process efficiency and performance; shorten the budget cycle, consolidate cost & compute models at speed
Plan your IT Financial Management journey with an established and Gartner recognised ITFM solution like MagicOrange.
