The role involves building and managing data pipelines, troubleshooting issues, and ensuring data accuracy across various platforms such as Azure Synapse Analytics, Azure Data Lake Gen2, and SQL environments.

This position requires extensive SQL experience and a strong background in PySpark development.

Responsibilities

Data Engineering:
- Work with Azure Synapse Pipelines and PySpark for data transformation and pipeline management.
- Perform data integration and schema updates in Delta Lake environments, ensuring smooth data flow and accurate reporting.
- Work with our Azure DevOps team on CI/CD processes for deployment of Infrastructure as Code (IaC) and Workspace artifacts.
- Develop custom solutions for our customers defined by our Data Architect and assist in improving our data solution patterns over time.

Documentation:
- Document ticket resolutions, testing protocols, and data validation processes.
- Collaborate with other stakeholders to provide specifications and quotations for enhancements requested by customers.

Ticket Management:




- Monitor the Jira ticket queue and respond to tickets as they are raised.
- Understand ticket issues, utilizing extensive SQL, Synapse Analytics, and other tools to troubleshoot them.
- Communicate effectively with customer users who raised the tickets and collaborate with other teams (e.g., FinOps, Databricks) as needed to resolve issues.

Troubleshooting and Support:
- Handle issues related to ETL pipeline failures, Delta Lake processing, or data inconsistencies in Synapse Analytics.
- Provide prompt resolution to data pipeline and validation issues, ensuring data integrity and performance.

Desired Skills & Requirements

Seeking a candidate with 5+ years of Dynamics 365 ecosystem experience with a solid PySpark development background. While various profiles may apply, we highly value a strong person-organization fit.

Our ideal candidate possesses the following attributes and qualifications:
- Extensive experience with

📌 Azure Data Integration Engineer (Pune)
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