Data Engineer (MLOps / Analytics Focus)

Blue Pearl PTY

Johannesburg

Presencial

Tempo integral

14 dias+
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Descrição da oferta de emprego

Johannesburg, South Africa | Posted on 05/21/2026

Our client is seeking a capable intermediate-level Data Engineer with strong MLOps and analytics experience to support the design, optimisation, governance, and monitoring of enterprise data and machine learning pipelines.

The successful candidate will play a critical role in ensuring scalable, sustainable, and efficient data processes while supporting analytics, ML model deployment, integrations, and reporting initiatives within a Databricks ecosystem.

This opportunity offers strong long-term potential, as contractors are typically retained for multi-year engagements.

Key Responsibilities
  • Design, optimise, and maintain scalable data pipelines within Databricks.
  • Ensure pipelines are efficient, sustainable, easy to debug, and user-friendly.
  • Implement and maintain Delta Tables and Databricks notebooks.
  • Perform data validation and basic data quality checks.
  • Monitor and improve process governance and operational efficiency.
  • Train, deploy, and monitor machine learning models using MLflow.
  • Analyse model performance and business impact.
  • Support model lifecycle management and deployment best practices.
Analytics & Reporting
  • Develop Power BI dashboards and business insight reporting.
  • Support data-driven decision-making through analytics solutions.
Integrations & Monitoring
  • Monitor API data integrations and data sends.
  • Troubleshoot integration failures and ensure data consistency.
Git-based Workflows
  • Pull requests
  • Branch syncing
  • Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders.
Qualifications

Degree or Diploma in:

  • Computer Science
  • Information Systems
  • Mathematics
  • Statistics
  • or related field
Experience
  • 3–5 years’ experience in Data Engineering or related roles.
  • Hands-on experience with Databricks.
  • Experience with MLflow and machine learning deployment processes.
  • Experience with Power BI dashboard development.
  • Strong experience with Git version control workflows.
  • Exposure to API integrations and monitoring.
Technical Skills
  • Databricks
  • Databricks Notebooks
  • MLflow
  • Python
  • SQL
  • Power BI
  • API Monitoring & Integration
  • Data Quality & Governance
Advantageous Skills
  • CI/CD for ML Pipelines
  • Spark / PySpark
  • Cloud-based data platforms
Soft Skills
  • Strong analytical and problem-solving abilities
  • Ability to work in collaborative environments
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