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Scope:

The Fabric Data Engineer will lead the design, development, integration and optimisation of enterprise data solutions across cloud and on-premises platforms. The role is responsible for building robust ETL/ELT pipelines, managing structured and semi-structured data assets, supporting analytics and reporting outcomes, and partnering with Business Analysts and stakeholders to translate business needs into secure, scalable and supportable data engineering solutions.

Key Responsibilities

• Own the structuring, development and ongoing management of in-house data construction, data integration and data management activities.

• Design, build and enhance ETL/ELT pipelines across multiple data sources using technologies such as Microsoft Fabric, SSIS, Azure Data Factory and Azure Functions / Function App.

• Integrate, transform and analyse data from relational, cloud and NoSQL platforms, including Azure SQL, Azure Blob Storage and MongoDB.

• Partner with Business Analysts, application teams and business stakeholders to understand technical and business requirements and convert them into data engineering deliverables.

• Develop and maintain data models, database objects, stored procedures and reusable data transformation logic using SQL and relevant programming languages.

• Implement data quality checks, reconciliation controls, performance tuning and exception handling to improve reliability and operational stability.

• Participate in end-to-end project delivery using hybrid and agile delivery methodologies, including estimation, solution design, build, testing, deployment and hypercare.

• Support reporting and analytics platforms such as Microsoft Fabric and SSRS by enabling trusted, governed and fit-for-purpose datasets.

• Prepare and maintain technical documentation, data lineage details, operational runbooks and knowledge transfer materials for BAU support.

• Provide technical guidance, troubleshooting and root-cause analysis for complex production data issues.

Domain Experience

• Prior experience as a Data Engineer or in a similar senior technical data role.

• Experience in one or more relevant domains such as CRM, Big Data, Business Intelligence, analytics reporting, enterprise data integration or data management.

• Exposure to stakeholder-facing delivery where technical solutions must be aligned to business outcomes.

• This senior position emphasises building ETL/ELT pipelines, managing diverse data platforms and collaborating closely with business stakeholders to deliver scalable data engineering solutions

Experience & Qualifications

• Bachelor's or master's degree in information technology, Computer Science, Engineering, Data Science or a related discipline.

• Data engineering, cloud or Microsoft technology certifications will be an advantage

• 3+ Years of experience in leading enterprise data solution design and implementation experience across cloud and on-premises systems.

Skill Area

Expected Capability

Priority

- Data Engineering: ETL/ELT design, data transformation, data modelling, data mining and segmentation techniques.

- Microsoft Cloud Data Stack: Azure Data Factory / Data Pipeline, Dataflows Gen2, SSIS, Azure Functions / Function App, Azure SQL, Azure Blob Storage and Microsoft Fabric.

- Database & Querying: Strong SQL skills, database design, performance tuning and hands-on experience with relational database platforms.

- Programming: Working knowledge of Python (Notebook - PySpark) and C# for data processing, automation and integration use cases.

- Reporting & Analytics: Experience with SSRS and exposure to BI / analytics reporting environments.

- Data Platforms: Experience with NoSQL and cloud-based storage or data platforms.

- Delivery Methods: Knowledge of end-to-end project delivery, hybrid and agile ways of working.

- Certifications: Relevant data engineering, cloud, Microsoft Fabric or Azure certifications.