Job details:

We are looking for an experienced Senior Data Engineer to support enterprise-scale data transformation and migration initiatives. The role focuses on modernizing legacy data platforms and delivering robust, scalable cloud-based solutions using Microsoft Azure technologies.

The ideal candidate will bring strong technical expertise, hands-on cloud experience, and the ability to design and implement high-performance data architectures.

Scope:

• Design and implement scalable data engineering solutions in Microsoft Azure.
• Lead and support data migration projects from legacy systems to cloud-based architectures.
• Develop and optimize large-scale data processing workflows using PySpark and Azure Databricks.
• Build and maintain data integration and migration pipelines using Informatica (PowerCenter and other Informatica tools).
• Design and manage data solutions leveraging Azure Data Factory, Azure Data Lake, and Azure SQL.
• Administer and optimize Azure Databricks environments for engineering workloads.
• Ensure data quality, performance optimization, and best practices in data architecture.
• Collaborate with cross-functional teams including architects, analysts, and DevOps engineers.
• Implement CI/CD pipelines and deployment workflows using Azure DevOps.
• Contribute to documentation, governance, and continuous improvement of data platforms.

Skills:

• 5+ years of experience in Data Engineering within enterprise environments.
• Strong experience in data migration and modernization projects.
• Hands-on experience designing and delivering solutions on Microsoft Azure.
• Proven experience with Informatica PowerCenter.
• Practical experience with Azure Databricks (administration and data engineering workloads).
• Strong knowledge of PySpark for large-scale data processing and transformation.
• Solid understanding of Azure Data Factory, Azure Data Lake, and Azure SQL.
• Proficiency in SQL and Python.
• Experience with Azure DevOps (CI/CD pipelines, version control, deployment workflows).

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