Digile
Website:
digile.com
Job details:
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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