Data Platform Engineer

Key Responsibilities

• Provide BAU support for the Enterprise Data Warehouse (EDW), including monitoring, troubleshooting, performance tuning, and issue resolution
• Support Qlik Replicate processes and ensure reliable data ingestion across systems
• Implement enhancements and modification requests to the EDW based on business needs
• Perform data validation, quality checks, and root cause analysis for data issues
• Ensure operational stability, security, and performance of live data pipelines and applications
• Document processes, configurations, and support procedures to maintain platform resilience

Project & Modernization Exposure While this is primarily a BAU-focused role, the Data Platform Engineer will also:

• Contribute to the migration of the EDW to Microsoft Fabric
• Gain exposure to modern cloud data technologies and evolving data architecture patterns
• Support development work related to platform modernization initiatives
• Work under the guidance and mentorship of senior data engineers on strategic transformation efforts.
• Follow coding best practices and ensure that the development works comply with the best practice guidelines.

Maintenance & continuous improvement

• Perform ITIL Incident, Problem, and Change Management practices in accordance to SLAs and follow processes.
• Identify key problem areas within the application and implement improvements. Evaluate and improve existing data analytics systems

Data Expertise

• Understand the IB’s main business processes and how it relates to data that is generated or captured.
• Understand associated data flows and dependencies between different enterprise systems ‍
• Required to independently research, test and problem-solve for technical issues or blockers, obtaining guidance from Leads or Architects when required. ‍
• Drive the troubleshooting of key technical issues or escalate and work with appropriate teams. ‍
• Identify key improvement areas and discuss with the technical lead where needed.
• BSc/BA in Computer Science, Engineering or relevant field
• Building the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources, applications and platforms.
• Able to integrate multiple data sources & user-end applications with databases into one system. (to store the data and its retrieval from the databases)
• Experience in designing and implementing robust data pipelines and ETL/ELT framework
• Proven experience as a data warehouse developer, including full implementation of data warehousing solution.
• Experience in data engineering solutions built on modern data lake or Lakehouse architectures, including Delta Lake or equivalent frameworks e.g. Microsoft Fabric
• Good understanding of enterprise design concepts: re-usability, continuous integration, security, scheduling, monitoring, etc
• In-depth understanding of database management systems, online analytical processing (OLAP), SQL queries (Azure SQL DB)
• Expertise with Azure Resource Management and templates is an added advantage
• Exposure to cloud technologies (MS Azure, AWS) & desire to learn and deliver new things on a needs-basis. (big data, BI, data science, etc.)
• Expertise in data warehouse design methodologies and technologies, data modelling (Data Vault modelling methodology experience is preferable), data quality and metadata
• Effective oral, written communication and presentation skills.
• Strong interpersonal skills. Self-motivated with a keen attention to detail and quality of work.

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[email protected]