Data Engineer

DLK Group; Eersterivier; Hybrid; ZAR 480,000 - 720,000; Full time

Benefits offered by this job

Hybrid working option

Job summary

DLK Group seeks a Data Engineer to design scalable data solutions, pipelines, and dashboards to support analytics and business decisions.

You will translate business requirements into technical architectures, implement ETL using Azure Data Factory, and build Power BI semantic models.

Responsibilities include data warehousing, SQL development, performance monitoring, and documentation, with hybrid working options.

Qualifications

• Matric essential.
• Degree in Computer Science / Engineering / Mathematics or related discipline.
• 10+ years relevant experience; practical component considered.

Responsibilities

• Develop and maintain ETL/data pipelines.
• Create Power BI reports and semantic models.
• Design data warehouse schemas with facts and dimensions.
• Write complex SQL / T-SQL for data extraction.
• Monitor and optimize data pipelines for performance.
• Document architectures and ETL workflows.
• Provide daily support for BI solutions.

Skills

Data engineering

ETL pipelines

SQL / T-SQL

Power BI

Data warehousing

Data modeling

Azure cloud

Architecture design

Batch processing

Education

Matric

Degree in Computer Science / Engineering / Mathematics

10+ years relevant experience

Tools

ADF (Azure Data Factory)

Power BI

Job description

We are looking for a Data Engineer to join our team. They will be responsible for creating scalable data solutions to support data-intensive applications and analytics. This includes not only the technical development of data pipelines and reports but also overseeing data engineering projects and contributing to the strategic direction of data initiatives within the organization.

Requirements

Technical Solution DevelopmentTranslate business requirements into technical data solutions. Participate in and contribute to architectural forums within the Business Intelligence (BI) team.Design and implement ETL/data pipeline architectures using tools like ADF (Azure data factory).Automate processes and design system architectures.Develop and manage Power BI semantic models, including understanding DAX queries and cubes.Visualization and Dash boarding: translate metrics into visual Power BI reportsIntegrate data between legacy and modern systems.Create ad-hoc SQL scripts to support user queries.Deploy and manage data solutions on cloud platforms like Azure.Data Modeling and ManagementUnderstanding of Data Warehouse modeling and Techniques: Data schemas, Facts, dimensions and building data warehouses.Writing complex SQL queries, joins, views and stored procedures to extract and manipulate data.Apply knowledge and practical experience in the Data Warehouse Life Cycle.Perform data modeling including dimensional, multi-dimensional, and relational models.Utilize TSQL for database management and querying.Support batch processing and scheduling tasks.Documentation and SupportCreate and maintain technical documentation such as data architecture diagrams, ETL workflows, and system documentation to ensure maintainability.Participate in design, peer, and code reviews.Provide daily technical, functional, and operational support for existing BI solutions.

Monitoring and Optimization

Monitor data pipeline and infrastructure performance.Identify bottlenecks and optimize for scalability, reliability, and cost-efficiency.Troubleshoot and resolve data-related issues.

Strategic and Emerging Technology Contributions

Contribute to evolving the architecture towards modern platforms, whether on-premise or cloud-based. Maintain working knowledge of Power BI reporting. Ensure technical skills stay relevant to emerging industry trends and organizational strategies, including Azure Cloud Solutions and Artificial Intelligence initiatives.

Desired Experience & Qualification

Qualifications:

• Matric essential
• Degree in Computer Science / Engineering / Mathematics or related discipline (could be replaced with 10+ years relevant experience)
• 4-5 years total experience (some experience may be replaced by post graduate qualifications if the practical component was relevant)

Desired Experience:

• Data Engineering
• Data pipeline architecture and development
• ETL architecture and implementation
• Azure Data Factory (ADF)
• Process automation
• Integration between legacy and modern systems
• Batch processing and scheduling
• Data Warehouse lifecycle

SQL / Database Technologies

• Advanced/complex SQLT-SQLSQL joinsViewsStored proceduresDatabase querying and managementAd-hoc SQL scripting

Data Warehousing & Data Modeling

• Data Warehouse modelling techniquesData schemasFacts and dimensionsData Warehouse constructionDimensional modellingMulti-dimensional modellingRelational modelling

Power BI / Business Intelligence

• Power BI reportingPower BI semantic modelsDAX queriesCubesPower BI visualization and dashboard developmentTranslating business metrics into visual reports

Cloud / Azure

• Deploying data solutions on AzureManaging cloud-based data solutionsAzure Cloud SolutionsUnderstanding the evolution from on-premise to modern/cloud-based architectures

Architecture

• Data/system architectureDesigning scalable data solutionsArchitectural forums within a BI environmentModernising architectureArchitecture diagrams and technical documentation

Benefits

• Hybrid working option