MLOps Data Engineer: Databricks Pipelines&Analytics, Johannesburg

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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