Data engineer at DLK Group – Eersterivier | Jobyssey

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 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 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

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