Data Engineer

Matisaar Technologies; Sandton; On-site; ZAR 900,000 - 1,300,000; Full time

Job summary

Matisaar Technologies in Sandton is seeking a Senior Azure Data Engineer to design, develop, and maintain enterprise-scale data platforms on Microsoft Azure and Fabric. You will build scalable ETL/ELT pipelines, implement data governance, and deliver analytics-ready datasets for BI.

The role requires hands-on expertise with Azure Data Factory, Databricks, PySpark, Synapse, ADLS Gen2, and Delta Lake, plus strong collaboration with data scientists, architects, data engineers and business

Qualifications

• 6+ years of experience in Data Engineering.
• Bachelor's Degree in Computer Science, IT, Engineering, or related field.
• Strong hands-on experience with Azure Data Factory, Azure Databricks, PySpark, Azure Synapse, and Microsoft Fabric.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Fabric Data Factory, and Azure Databricks.
• Build metadata-driven and parameterized pipeline frameworks for reusable and scalable data integration.
• Develop batch and near real-time ingestion pipelines from databases, APIs, flat files, and streaming platforms.
• Implement CDC and incremental loading strategies for efficient data processing.

Skills

6+ years Data Engineering

Education

Bachelor's Degree in Computer Science/IT/Engineering

Tools

Azure Data Factory

Azure Databricks

PySpark

Azure Synapse

Microsoft Fabric

Delta Lake

ADLS Gen2

Job description

Matisaar Technologies is a global Product Engineering and IT Services organization with

operations & presence in India & South Africa. We cater to a diverse portfolio of clients across industries including

Banking & Financial Services, Agriculture, Education, Insurance, HR, Supply Chain. Our expertise lies in designing and

delivering cutting-edge technology solutions that enhance business performance, improve user experiences, and enable digital transformation.

About the Role

We are looking for a highly skilled Senior Azure Data Engineer with strong experience in designing, developing, and maintaining enterprise-scale data platforms on Microsoft Azure and Microsoft Fabric. The ideal candidate should possess expertise in Azure Data Factory, Azure Databricks, PySpark, Azure Synapse Analytics, ADLS Gen2, Delta Lake, Medallion Architecture, and modern data warehousing solutions. The role involves building scalable ETL/ELT pipelines, implementing data governance frameworks, and delivering analytics-ready datasets for business intelligence and reporting

• Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Fabric Data Factory, and Azure Databricks.
• Build metadata-driven and parameterized pipeline frameworks for reusable and scalable data integration.
• Develop batch and near real-time ingestion pipelines from databases, APIs, flat files, and streaming platforms.
• Implement CDC and incremental loading strategies for efficient data processing.

Data Lake & Data Warehouse Implementation

• Design and implement enterprise data lake solutions using ADLS Gen2, OneLake, and Delta Lake.
• Build and maintain Medallion Architecture (Bronze, Silver, Gold) for governed and analytics-ready datasets.
• Develop and optimize enterprise data warehouses using Azure Synapse Analytics.
• Create dimensional models, fact tables, and dimension tables based on business requirements.

Data Transformation & Processing

• Develop complex business transformations using PySpark, Spark SQL, SQL, T-SQL, and Mapping Data Flows.
• Process high-volume structured and semi-structured data sources.
• Design scalable data transformation frameworks to support reporting and advanced analytics.

Data Integration

• Integrate data from REST APIs, Oracle, SQL Server, PostgreSQL, flat files, Kafka, and third-party applications.
• Support hybrid data integration between on-premises and cloud environments.
• Build centralized analytics platforms consolidating enterprise-wide data domains.

Data Quality & Governance

• Implement data validation, reconciliation, auditing, and exception-handling frameworks.
• Enforce data governance, security, lineage, and metadata management using Azure Purview.
• Ensure adherence to enterprise compliance requirements and data management standards.
• Implement RBAC, Managed Identities, and Key Vault-based security controls.

Performance Optimization

• Optimize Spark workloads, Delta Lake tables, SQL queries, partitioning strategies, and storage structures.
• Improve scalability, reliability, and cost efficiency across Azure data platforms.
• Troubleshoot and resolve performance bottlenecks in pipelines and analytical workloads.

Monitoring & Support

• Build end-to-end monitoring and alerting solutions using Azure Monitor and Log Analytics.
• Implement production support processes, incident management, and root cause analysis.
• Ensure pipeline reliability, SLA compliance, and operational excellence.

BI & Analytics Enablement

• Create curated datasets for Power BI reporting and self-service analytics.
• Support business intelligence teams with high-quality, analytics-ready data.
• Enable customer analytics, operational reporting, financial reporting, and executive dashboards.
• Implement CI/CD pipelines using Azure DevOps and GitHub Actions.
• Manage source control, release management, and deployment automation.
• Collaborate with architects, analysts, data scientists, business stakeholders, and product teams.
• Participate in Agile ceremonies, code reviews, sprint planning, and technical design sessions.

Preferred Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or related field.
• 6+ years of experience in Data Engineering.
• Strong hands-on experience with Azure Data Factory, Azure Databricks, PySpark, Azure Synapse, and Microsoft Fabric.
• Experience implementing enterprise data lakes and data warehouse modernization projects.
• Experience working with telecom, banking, healthcare, finance, or large enterprise data ecosystems.
• Microsoft Azure Certifications (DP-203, AZ-900) preferred.