Senior Data Engineer – Healthcare Data Platform
Listed on 2026-10-10
-
IT/Tech
Data Engineering
We are seeking a Senior Data Engineer to join a greenfield/future-state data platform initiative within the healthcare and medical scheme administration environment.
The successful candidate will be responsible for owning delivery end-to-end, from discovery and assessment through to implementation. This is a highly autonomous role requiring strong technical depth across both legacy data technologies and modern cloud data platforms
.
The environment includes POPIA-sensitive health data
, with a legacy estate incorporating Oracle, SAP Business Objects and SAS, while the organization transitions towards a modern cloud-based data environment.
We are seeking a Senior Data Engineer to join a greenfield/future-state data platform initiative within the healthcare and medical scheme administration environment.
The successful candidate will be responsible for owning delivery end-to-end, from discovery and assessment through to implementation. This is a highly autonomous role requiring strong technical depth across both legacy data technologies and modern cloud data platforms
.
The environment includes POPIA-sensitive health data
, with a legacy estate incorporating Oracle, SAP Business Objects and SAS, while the organization transitions towards a modern cloud-based data environment.
- Position: Senior Data Engineer
- Contract: Up to 18 months, structured in 6-month phases
- Start Date: 1 October 2026
- Work Model: Hybrid
- Location: Waterfall / Midrand / Johannesburg
The ideal candidate should have strong hands-on experience with:
- Oracle Database
- Advanced SQL development and optimisation
- SAP Business Objects (BO)
- SAS
- Power BI
- Data profiling and quality assessment
- ETL and data engineering
- Process automation
- Self-service analytics
- Snowflake
- AWS
- Data modelling
- Metadata management and data cataloguing
- Generative AI / LLM applications
The Senior Data Engineer will operate as a self-sufficient technical lead
, independently driving delivery and managing the engagement from discovery through implementation.
The primary objective is to reduce operational workload across the client's reporting estate through:
- Reporting rationalisation
- Process automation
- Self-service enablement
- Data quality automation
- Reusable data assets
- Improved governance and metadata management
Success will be measured by business outcomes, operational efficiency and released capacity
, rather than simply utilisation.
- Assess and baseline the current reporting landscape.
- Analyse complex and potentially undocumented data environments.
- Identify manual, repetitive and inefficient processes.
- Quantify effort and operational workload.
- Prioritise initiatives based on measurable effort reduction and business value.
- Review the existing reporting estate.
- Identify opportunities to retire, consolidate and standardise reports.
- Establish consistent metric and data definitions.
- Reduce duplication and unnecessary reporting effort.
- Design and implement robust ETL/data engineering solutions.
- Automate manual and repetitive processes.
- Develop automated validation, reconciliation and quality assurance controls.
- Implement appropriate audit trails and controls.
- Improve data reliability and operational efficiency.
- Develop reusable datasets and data products.
- Enable business users through governed Power BI assets.
- Promote appropriate self-service analytics while maintaining data governance.
- Establish and maintain a centralised reporting/data catalogue.
- Define metadata standards.
- Improve discoverability and understanding of reporting assets.
- Explore appropriate use of Generative AI/LLMs for…
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