Posted on: 22/06/2026
Job Description :
The selected candidate will be responsible for supporting a large-scale enterprise data migration initiative involving the modernization and migration of legacy/on-premises data platforms into Azure Databricks.
The role requires strong technical depth, independent problem-solving capabilities, and hands-on experience in designing and implementing scalable data engineering solutions.
Key Responsibilities :
- Design and build scalable, optimized ETL pipelines using Databricks, PySpark, and SQL.
- Ingest, transform, and load data from Oracle and other source systems into Azure-based data platforms.
- Review and validate source-to-target mappings and data schema designs.
- Develop data marts and aggregated analytical layers to support Power BI dashboards and enterprise reporting.
- Implement robust logging, monitoring, data validation, reconciliation, and error-handling frameworks.
- Convert and migrate scheduled reporting workloads into Databricks notebook/workflow-based reporting solutions.
- Collaborate with architecture, analytics, reporting, and business teams to ensure successful project delivery.
Mandatory Skills :
- Databricks
- PySpark
- SQL
- Azure Data Factory (ADF)
- Azure Data Lake / Lakehouse Architecture
- Data Engineering & ETL Development
- Power BI Integration & Reporting
Candidates must have hands-on experience in :
- On-Premises to Cloud Databricks Migration Projects
- Enterprise Data Platform Modernization Programs
- Azure Data Engineering Ecosystem
- Large-scale ETL/ELT Pipeline Development
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1647341