IT Data Engineer

Job Advert Summary

Feltex is seeking a skilled and motivated IT Data Engineer to design, develop, maintain, and support reliable, scalable, and governed data solutions. The IT Data Engineer will play a key role in building and maintaining data pipelines, integrating and transforming data, and ensuring high levels of data quality, integrity, and security. Working closely with business, IT, OT, and engineering stakeholders, the IT Data Engineer will enable accurate reporting, analytics, and data-driven decision-making by delivering accessible and trusted data solutions that support both operational and strategic objectives.

Minimum Requirements

• Must be in possession of a school leaving Certificate (Grade 12)
• Diploma: Information Technology
• Minimum 5 years’ experience in similar role

Duties & Responsibilities

IT Strategy:

• Provide input to the IT Strategy of Feltex in line with business requirements
• Identify, mitigate and manage IT Risk

Data Engineering:

• Design, build and maintain data pipelines that support reliable movement of data from local business systems into Microsoft Fabric.
• Develop data models, lakehouse structures and reporting datasets that support operational, financial and management reporting requirements.
• Transform and prepare data for reporting, analytics and business decision-making.
• Integrate data from ERP, MES, SCADA, IoT, CMMS and other business or operational systems where applicable.
• Support batch, scheduled, near real-time and streaming data ingestion patterns where required by business or operational reporting needs.
• Monitor data pipelines and resolve failures, data load issues and processing exceptions.
• Optimise data pipelines and models for performance, reliability, maintainability and cost efficiency.
• Develop reusable and governed data products that can be consumed by reporting, analytics and business process improvement initiatives.
• Maintain technical documentation for data sources, pipelines, transformations, models and reporting datasets.

Data Governance:

• Support the implementation of data ownership, stewardship and classification across business data domains.
• Maintain data lineage and traceability from source systems through ingestion, transformation and reporting layers.
• Apply agreed data standards, naming conventions and validation rules across data engineering solutions.
• Identify and escalate data quality issues, duplicate records, incomplete data and control weaknesses.
• Support audit evidence requirements for data movement, access control, change management and information security controls.

Fabric Migration:

• Assist with the migration of local data sources, legacy extracts and reporting processes into Microsoft Fabric.
• Support the design and maintenance of Fabric lakehouse, warehouse, pipeline and semantic model components.
• Contribute to scalable lakehouse, warehouse and data platform architecture that supports reusable data products and governed analytics.
• Validate migrated data against source systems to confirm completeness, accuracy and consistency.
• Work with business users, IT, OT, engineering and analytics stakeholders to prioritise migration activities, data product requirements and reporting needs.
• Support the reduction of manual spreadsheets, duplicated reports and uncontrolled local data stores.

Reporting and Analytics:

• Develop and maintain reliable reporting datasets for business intelligence and operational reporting.
• Support Power BI reporting by preparing accurate, structured and governed data models.
• Assist business users with reporting requirements, data definitions and interpretation of available data.
• Support reporting and analytics for manufacturing and operational KPIs, including OEE, downtime, yield, throughput, asset reliability, supply chain efficiency, safety and sustainability where applicable.
• Review reports and datasets to identify improvement opportunities, inconsistencies and obsolete content.
• Ensure reporting outputs are aligned with approved data sources and business rules.

IT Security:

• Apply least-privilege access to data platforms, pipelines, Fabric workspaces and reporting datasets.
• Maintain data classification, ownership and lineage when migrating local data into Microsoft Fabric.
• Protect confidential, personal and business-critical data across pipelines, lakehouses, models and reports.
• Maintain audit trails for data movement, transformations, access changes and administrative activities.
• Escalate unauthorised access, data security incidents, data quality risks and control weaknesses.

Policies, Procedures:

• Abide by the IT Policies and Procedures
• Recommend changes to the IT Policies, Procedures, Standards, Protocols, Work Instructions, etc.

Administration:

• Compile IT Reports
• Participate in software and licence discussions to ensure appropriate tools are selected, licensed, and aligned with business and data requirements.

People Management:

• Ensure an enabling climate/culture