Data Platform Engineer

Digile; Hyderabad; On-site; INR 1,200,000 - 2,300,000; Full time

Job summary

Digile is seeking an experienced Data Platform Engineer to manage BAU operations of the Enterprise Data Warehouse (EDW), troubleshoot data issues, and improve performance. You will work on data pipelines, ETL/ELT processes and platform modernization including Microsoft Fabric.

Ideal candidates will have strong SQL skills, knowledge of Azure data services, and hands-on experience with data lakehouse architectures.

Qualifications

• BAU support for the Enterprise Data Warehouse (EDW) including monitoring and troubleshooting.
• Experience with data validation and data quality checks.
• Familiarity with ITIL incident, problem and change management practices.

Responsibilities

• Provide BAU support for the EDW including monitoring, troubleshooting, performance tuning, and issue resolution.
• Support data ingestion across systems and ensure reliable data flow via Qlik Replicate.
• Implement enhancements to the EDW based on business needs.
• Perform data validation, quality checks and root-cause analysis for issues.
• Ensure operational stability, security, and performance of live data pipelines.

Skills

Data warehousing

Data pipelines

ETL/ELT

Azure SQL DB

Delta Lake

Microsoft Fabric

Qlik Replicate

ITIL practices

SQL queries

Cloud platforms

Education

BSc/BA CS or related field

Tools

Qlik Replicate

Azure

Delta Lake

Microsoft Fabric

Azure Resource Manager templates

Job description

We are looking for an experienced Data Platform Engineer with strongexpertisein data warehousing, data pipelines, ETL/ELT, and platform support. The ideal candidate will manage BAU operations, troubleshoot data issues, ensure platform performance and reliability, and deliver enhancements based on business needs.

The role also offers exposure to modern data platforms and migration initiatives, including Microsoft Fabric and Lakehouse architectures. Strong problem-solving, data validation, ITIL practices, documentation, and collaboration skills are essential.

• 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 tomaintainplatform 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.
• Followcodingbest 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 accordancetoSLAs and follow processes.
• Identifykey problem areas within the application and implement improvements. Evaluate and improve existing data analytics systems

Data Expertise

• Understand the IB’smain businessprocesses 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 withappropriate teams.
• Identifykey improvement areas and discuss with the technical lead where needed.
• Building the infrastructure required foroptimalextraction, transformation, and loading of data from a wide variety of data sources,applicationsand 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)
• Expertisewith 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.)
• Expertisein data warehouse design methodologies and technologies, data modelling (Data Vault modellingmethodologyexperience is preferable), data quality and metadata
• Skills/Other Details
• Effective oral, written communication and presentation skills.
• Strong interpersonal skills. Self-motivated with a keen attention to detail and quality of work.
• BSc/BA in Computer Science,Engineeringor relevant field