Data Engineer

dlk; Cape Town; Hybrid; ZAR 700,000 - 900,000; Full time

Benefits offered by this job

Hybrid working option

Job summary

dlk is seeking a Data Engineer to design scalable data pipelines and BI solutions in a hybrid working setup. You will develop ETL architectures using ADF, build Power BI semantic models, and automate processes while aligning with strategic data initiatives.

Responsibilities include data modeling, complex SQL development, and documentation. The role requires Azure deployment experience and collaboration across BI teams.

Qualifications

• Experience translating business requirements into technical data solutions.
• Proven ability to design and implement ETL/data pipeline architectures.
• Hands-on SQL development and data modeling expertise.
• Experience deploying data solutions on Azure and building BI models.

Responsibilities

• Translate business needs into scalable data solutions and pipelines.
• Develop and manage Power BI semantic models and dashboards.
• Contribute to architecture forums within the BI team.
• Monitor pipeline performance and optimize for cost-efficiency.
• Create technical docs: data architecture, ETL workflows, system docs.

Skills

Data engineering

ETL architecture

Azure Data Factory

Process automation

Power BI reporting

DAX queries

SQL / Database technologies

T-SQL

Data warehousing & modeling

Cloud / Azure

Architecture diagrams

Education

Matric essential Degree in Computer Science / Engineering / Mathematics or related discipline

Tools

ADF (Azure Data Factory)

Power BI

SQL Server / Azure SQL

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 Development

Translate 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 reports Integrate 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 Management Understanding 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 Support Create 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 optimise 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 organisational 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 SQL
• T-SQL
• SQL joins
• Views
• Stored procedures
• Database querying and management
• Ad-hoc SQL scripting
• Data Warehousing & Data Modeling
• Data Warehouse modelling techniques
• Data schemas
• Facts and dimensions
• Data Warehouse construction
• Dimensional modelling
• Multi-dimensional modelling
• Relational modelling
• Power BI / Business Intelligence
• Power BI reporting
• Power BI semantic models
• DAX queries
• Cubes
• Power BI visualization and dashboard development
• Translating business metrics into visual reports
• Cloud / Azure
• Deploying data solutions on Azure
• Managing cloud-based data solutions
• Azure Cloud Solutions
• Understanding the evolution from on-premise to modern/cloud-based architectures
• Architecture
• Data/system architecture
• Designing scalable data solutions
• Architectural forums within a BI environment
• Modernising architecture
• Architecture diagrams and technical documentation

Benefits

• Hybrid working option