Senior Data Engineer

Blue Pearl PTY; Johannesburg; Hybrid; ZAR 900,000 - 1,300,000; Full time

Job summary

Medscheme in Johannesburg is seeking a Senior Data Engineer to lead a greenfield data platform initiative in a healthcare setting. The role focuses on building an MVP, establishing architecture standards, and enabling scalable data ingestion, modeling and automation for sensitive health data.

You will work independently in a delivery-driven environment, applying strong data engineering practices, DataOps, and security governance to deliver robust analytics capabilities and a Power BI reporting

Qualifications

• Direct, practical experience across the modern cloud data engineering stack.
• Hands-on design and implementation of scalable data platforms.
• Strong data modelling and SQL capabilities.

Responsibilities

• Design and build the future-state data platform MVP with scalable pipelines.
• Develop automated ingestion and integration patterns and Snowflake models.
• Develop transformations using dbt and implement CI/CD for analytics engineering.
• Establish DataOps, data quality checks and monitoring for reliability.
• Support migration to target-state architecture and Power BI layer.
• Transfer knowledge to Medscheme teams and ensure governance and security.

Tools

Snowflake

dbt

AWS

Fivetran

Power BI

Advanced SQL

CI/CD for analytics engineering

DataOps

Metadata management

Data integration

Job description

Johannesburg, South Africa | Posted on 09/02/2026

We are seeking an experienced Senior Data Engineer to join a high-impact greenfield data platform initiative within the healthcare and medical scheme administration environment.

This is a highly technical, delivery-focused role responsible for building the future-state MVP and establishing the foundational architecture, engineering standards and reusable patterns required to support the long-term scalability and automation of the data platform.

The successful candidate will be comfortable working independently, translating business and analytics requirements into robust technical solutions, and operating within a POPIA-sensitive health-data environment .

Key Responsibilities

• Design and build the future-state data platform MVP , including scalable data pipelines and transformation processes.
  
• Develop and implement automated data ingestion and integration patterns .
  
• Build robust and reusable Snowflake data models aligned to business and analytics requirements.
  
• Develop transformation workflows using dbt , applying modern analytics engineering practices.
  
• Implement data ingestion using Fivetran and establish reliable integration patterns.
  
• Design and implement automated data quality checks, testing and validation frameworks .
  
• Establish monitoring and controls to ensure data accuracy, reliability, availability and performance.
  
• Apply CI/CD practices across data and analytics engineering workflows.
  
• Implement and promote DataOps practices to improve automation, deployment, monitoring and operational reliability.
  
• Support migration from legacy reporting processes to the target-state data architecture .
  
• Establish reusable engineering standards, frameworks, patterns and documentation for future phases of the platform.
  
• Develop and support the Power BI reporting layer required for the MVP.
  
• Collaborate with business, analytics and technical stakeholders to translate requirements into scalable technical solutions.
  
• Ensure solutions are designed with appropriate security, governance, metadata management and POPIA considerations .
  
• Provide technical guidance and knowledge transfer to Medscheme staff , supporting the sustainable adoption of the new platform.
  
• Troubleshoot technical issues and continuously improve the performance, scalability and reliability of the data platform.
  

Requirements

Required Technical Skills

The successful candidate must have strong, hands-on experience with the following technologies and disciplines:

• Snowflake
  
• dbt
  
• AWS
  
• Fivetran
  
• Power BI
  
• Advanced SQL
  
• Automated data quality and testing
  
• CI/CD for analytics engineering
  
• DataOps
  
• Metadata management
  
• Data integration and pipeline development
  

Important: Candidates should have direct, practical experience across the required modern cloud data engineering stack. Adjacent or theoretical exposure will not be sufficient.

Candidate Profile

We are looking for a self-sufficient Senior Data Engineer who can take ownership of the technical build and deliver outcomes with minimal supervision.

The ideal candidate will:

• Have strong senior-level experience in modern cloud data engineering.
  
• Be highly proficient across the Snowflake, dbt, AWS and Fivetran technology stack.
  
• Have experience designing and implementing scalable data platforms and pipelines.
  
• Understand modern DataOps, CI/CD and automated data quality practices.
  
• Be capable of developing reusable frameworks and engineering standards rather than one-off solutions.
  
• Be comfortable translating business and analytics requirements into technical solutions.
  
• Have strong data modelling and SQL capabilities.
  
• Be able to work independently in a delivery-focused environment.
  
• Have strong problem-solving and analytical capabilities.
  
• Be comfortable working with sensitive and regulated data.
  
• Understand the importance of data governance, security, quality and metadata management.
  
• Be able to communicate effectively with both technical and non-technical stakeholders.
  
• Have the ability and willingness to transfer knowledge to internal Medscheme teams .
  
• Be outcome-oriented and accountable for delivering agreed technical outcomes.
  

The successful candidate will be expected to deliver:

• Snowflake-based data models and pipelines
  
• Automated data ingestion and transformation processes
  
• Automated testing and data quality controls
  
• Monitoring and reliability mechanisms
  
• Foundational architecture for future platform phases
  
• Reusable data engineering standards, frameworks and patterns
  
• Power BI reporting layer supporting the MVP
  
• Documentation and knowledge transfer to internal teams
  

The role will operate within a healthcare / medical scheme administration environment , where data may include sensitive health-related information. Strong attention to data security, governance, privacy and regulatory requirements is therefore essential.

Experience working with POPIA-sensitive or other regulated data environments will be highly advantageous.

Work Model: Hybrid

Contract Duration: 5 months

Start Date: 1 October 2026