Job Description
Minimum education (essential):
- BSc in Computer Science, Engineering or relevant field
Minimum applicable experience (years):
- 2-4 years
Required nature of experience:
- Experience with SQL Server and Azure Synapse Analytics/Microsoft Fabric for query writing, indexing, performance tuning and schema design.
- Hands-on experience developing ETL pipelines, including data extraction from REST/SOAP APIs, databases and flat files.
- Proficiency in data transformation using Python and Azure-native tools.
- Experience with data warehousing.
- Background in data modelling, including dimensional modelling, schema evolution and versioning.
- Practical knowledge of cloud-based data storage and processing using Azure Blob Storage.
- Familiarity with pipeline optimisation, fault tolerance, monitoring and security best practices.
- Experience developing web applications using C# and the .NET platform.
- Experience with front-end development using Blazor, React.js, JavaScript/TypeScript, HTML, CSS/SCSS.
Skills and Knowledge (essential):
- SQL Server, Azure Synapse Analytics, Azure Blob Storage, Microsoft Fabric
- Python
- REST/SOAP APIs, Data Extraction, Transformation, Loading (ETL)
- Azure Data Factory, Pipeline Orchestration
- Dimensional Modelling, Schema Evolution, Data Warehousing
- Power BI
- Performance Optimisation, Indexing, Query Tuning
- Cloud Data Processing, Backups
- C#, .NET, Blazor
- JavaScript/TypeScript, HTML, CSS/SCS
Other:
- Proficient in Afrikaans and English
- Own transport and license
KEY PERFORMANCE AREAS AND OBJECTIVES
ETL and Pipeline Development
- Design, build, and orchestrate efficient ETL pipelines using Azure Synapse for both batch and near-real-time data ingestion.
- Extract data from a variety of structured and unstructured sources including REST APIs, SOAP APIs, databases, and flat files.
- Apply robust data transformation logic using Python and native Azure Synapse transformation tools.
- Optimise data flows for performance, scalability, and cost-effectiveness.
- Implement retry mechanisms, logging and monitoring within pipelines to ensure data integrity and fault tolerance.
Data Architecture and Management
- Design and manage scalable and efficient data architectures using Microsoft SQL Server and Azure services, including Synapse Analytics/Microsoft Fabric and Blob Storage.
- Develop robust schema designs, indexes and query strategies to support analytical and operational workloads.
- Support schema evolution and version control, ensuring long-term maintainability and consistency across datasets.
- Implement and maintain metadata repositories and data dictionaries for improved data governance and transparency.
- Define and maintain role-based access control to ensure data security and compliance.
Data Warehousing and BI Integration
- Architect and manage enterprise data warehouses using Azure Synapse Analytics.
- Apply best practices for data loading, partitioning strategies, and storage optimisation.
- Integrate warehousing solutions with Power BI and other analytics platforms for seamless business intelligence consumption.
Data Modelling & Standards
- Develop and maintain conceptual, logical and physical data models.
- Implement dimensional modelling techniques (e.g., star/snowflake schemas) to support advanced analytics and reporting.
- Apply normalisation standards and relational modelling techniques to support OLTP and OLAP workloads.
- Ensure consistency of data models across systems and support schema versioning and evolution.
Reporting and Communication
- Provide clear, timely updates on task status and progress to senior developers / management.
- Contribute to reports, manuals, and other documentation related to software status, operation, and maintenance.
- Collaborate effectively with team members and stakeholders using the appropriate communication channels.
- Maintain system and product change logs and release notes according to company standards.
Automation, Monitoring and Optimisation
- Automate recurring data engineering tasks and deploy solutions with CI/CD best practices.
- Implement monitoring and alerting mechanisms to detect data quality issues and pipeline failures.
- Analyse and optimise query performance across platforms (SQL Server, Azure Synapse).
- Support scalability planning and cost control by monitoring pipeline execution and resource usage
Security and Best Practices
- Enforce security best practices for data access, including encryption and secure authentication.
- Ensure compliance with data governance policies and applicable regulatory standards.
- Document processes, architectural decisions and technical implementations in alignment with organisational standards
Contribution to The Team
- Collaborate with developers, data analysts, data scientists and business teams to understand data requirements and deliver scalable solutions.
- Work with the team to integrate pipelines with source control and deployment workflows
Quality Management and Compliance
- Document data processes, transformations and architectural decisions.
- Maintain high standards of software quality within the team by adhering to good processes, practices and habits.
- Ensure compliance to the established processes and standards for the development lifecycle, including but not limited to data archival.
- Safeguard confidential information and data.
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