Data Engineer

PBT Group is seeking a Data Engineer to join our Cape Town-based consulting team on a contract basis.

We are looking for a well-rounded end-to-end Data Engineer with solid practical experience across data warehousing, ETL development, SQL and the Microsoft data technology stack. The ideal candidate will be comfortable working across the full data engineering lifecycle - from understanding source systems and extracting data, through transformation and loading into data warehouse environments, to supporting downstream reporting and analytics requirements.

This is an ideal opportunity for a Data Engineer who has developed a strong foundation in traditional data engineering and data warehousing and is looking to further expand their experience across modern Microsoft/Azure data technologies.

Key Responsibilities

• Design, develop and maintain end-to-end data pipelines and ETL processes.

• Develop robust and reusable ETL solutions using the Microsoft data stack.

• Extract, transform and load data from multiple source systems into data warehouse environments.

• Develop and optimise complex SQL queries, stored procedures, views and data transformation logic.

• Design and implement data warehouse structures, including dimensional models, fact and dimension tables.

• Work with business and technical stakeholders to understand data requirements and translate these into effective data solutions.

• Perform data analysis, profiling and validation to ensure data quality and integrity.

• Develop, test and deploy data integration solutions across development, test and production environments.

• Troubleshoot and resolve data pipeline, ETL and data quality issues.

• Optimise existing ETL processes and SQL workloads for performance and scalability.

• Support the integration of on-premise and cloud-based data sources.

• Contribute to technical documentation, development standards and best practices.

• Work within Agile delivery teams and participate in planning, stand-ups, reviews and retrospectives.

• Collaborate with Data Architects, BI Developers, Analysts and other technical teams to deliver end-to-end data solutions.

Essential Technical Experience

Strong practical experience in:

• SQL / T-SQL

• Data Warehousing

• ETL / Data Integration

• SSIS

• SQL Server

• Relational databases and data modelling

• Dimensional modelling / Kimball methodology

• Data transformation and cleansing

• Stored procedures and complex SQL development

• Data quality and reconciliation

• Performance optimisation

Microsoft / Azure Stack

Experience with one or more of the following:

• Azure Data Factory (ADF)

• Azure SQL

• Azure Synapse Analytics

• Azure Data Lake / ADLS

• SQL Server Integration Services (SSIS)

• SQL Server Management Studio (SSMS)

• Power BI / SSAS exposure would be advantageous

ADF can also be used alongside existing SSIS workloads, including running SSIS packages through Azure-SSIS Integration Runtime, making a combination of traditional Microsoft ETL and Azure data integration experience particularly useful.

End-to-End Data Engineering Exposure

The successful candidate should be able to demonstrate experience across a meaningful portion of the following:

Source Systems → Data Ingestion → ETL → Data Transformation → Data Warehouse → Data Quality → Data Consumption

They should understand how the different components fit together rather than having experience limited to one particular area of the data lifecycle.

Advantageous Experience

• Azure cloud data engineering

• Azure Data Factory

• Azure Synapse

• Azure Data Lake

• Power BI

• SSAS

• Python

• REST APIs

• Git / Azure DevOps

• CI/CD and DevOps practices

• Data governance and lineage

• Metadata management

• Automated testing

• Exposure to modern cloud data platforms or Microsoft Fabric

Candidate Requirements

• Relevant tertiary qualification in Computer Science, Information Systems, Data Engineering, IT or a related field.

• Approximately 3-6 years' commercial Data Engineering experience.

• Strong hands-on experience in SQL and ETL development.

• Demonstrable experience working with data warehouse environments.

• Good understanding of data modelling and data integration principles.

• Experience working within structured development and release environments.

• Comfortable working independently while collaborating with Architects, Developers, Analysts and business stakeholders.

• Strong analytical and problem-solving abilities.

• Good communication and documentation skills.

• Exposure to Agile methodologies.

What We Are Looking For

The ideal candidate is not simply an ETL Developer. We are looking for someone who has progressed into a broader Data Engineering role, with a solid understanding of:

• How source systems provide data

• How data should be ingested and transformed

• How data warehouses are designed and populated

• How to build reliable and maintainable ETL pipelines

• How to troubleshoot and optimise data solutions

• How data ultimately supports BI, reporting and analytics

They should have a strong Microsoft foundation, particularly around SQL Server, SSIS and data warehousing, with Azure experience being highly advantageous.

This is a hands-on Data Engineering role suited to someone who can take ownership of development tasks while working within a broader consulting and delivery team.