Lakehouse Data Engineer | Azure Databricks & AI-ready Data

PBT Group; Johannesburg; On-site; ZAR 600,000 - 1,200,000; Full time

Job summary

PBT Group in Johannesburg is seeking an experienced Data Engineer to join a project implementing a modern Lakehouse architecture with the Medallion framework. You will build and maintain data ingestion pipelines, landing in Bronze, Silver, and Gold layers, and support semantic modelling for Power BI reporting and AI use cases.

Collaboration with Data Scientists and stakeholders will drive production deployment, governance and performance excellence.

Qualifications

• Hands-on Data Engineer with Azure Databricks expertise.
• Experience implementing Medallion/Lakehouse architectures (Bronze/Silver/Gold).
• Strong Python, PySpark and SQL proficiency for data engineering and transformations.
• Experience building and maintaining Azure Data Factory pipelines.
• Knowledge of data modelling, semantic modelling and warehousing principles.

Responsibilities

• Design, develop and maintain scalable data pipelines and Lakehouse architecture.
• Ingest data from multiple sources and ensure reliable landing, transformation and processing.
• Support semantic data modelling for Power BI reporting and analytics.
• Ensure data governance, quality, lineage and documentation across data products.
• Collaborate with Data Scientists and stakeholders in an Agile delivery environment.

Skills

Azure Databricks

Python

PySpark

SQL

Azure Data Factory

Medallion architecture

Data modelling

Data governance

Git & CI/CD

Agile

Education

Databricks Data Engineer Certification (preferred)

Tools

Databricks Unity Catalog

Azure Functions

Apache Kafka

Apache Spark

Job description

PBT Group in Johannesburg is seeking an experienced Data Engineer to join a project implementing a modern Lakehouse architecture with the Medallion framework. You will build and maintain data ingestion pipelines, landing in Bronze, Silver, and Gold layers, and support semantic modelling for Power BI reporting and AI use cases.

Collaboration with Data Scientists and stakeholders will drive production deployment, governance and performance excellence.