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
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• Required to independently research, test and problem-solve for technical issues or blockers, obtaining guidance from Leads or Architects when required.  
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• Drive the troubleshooting of key technical issues or escalate and work with appropriate teams.
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• 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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