Job Description

Key Responsibilities:
EXP: 8- 12YAER
Location - Hyderabad /Ahmedabad

• Optimize scalable data pipelines for ingestion, transformation, and loading of large datasets from diverse sources.
• Utilize Azure Data Factory for orchestration and automation of ETL/ELT processes, ensuring efficient data flow.
• Work extensively with Azure services such as Azure Blob Storage and Azure Data Lake Storage (ADLS Gen2) for efficient data storage and management.
• Integrate and manage data flows using Azure Logic Apps for event-driven automation and workflow orchestration.
• Develop and maintain robust SQL queries, stored procedures, and data models to support reporting and analytical requirements.
• Implement and enforce data governance, quality, and security best practices.
• Troubleshoot, debug, and optimize existing data pipelines and data infrastructure.

Key Skills :

• Proven experience as a Senior Data Engineer, with a strong emphasis on designing and implementing solutions, production support, Maintenance projects & Data Engineering applications on Azure and Snowflake cloud platforms.
• Mandatory: Expert-level proficiency with Snowflake for data warehousing and data platform development.
• Mandatory: In-depth knowledge and practical experience with the Azure data ecosystem, including:
• Azure Data Factory (ADF) for pipeline orchestration.
• Azure Blob Storage and Azure Data Lake Storage (ADLS Gen2) for data storage.
• Azure Logic Apps for workflow automation.
• Exceptional command of SQL for complex querying, data manipulation, and performance tuning.
• Familiarity with version control systems (e.g., Git).
• Excellent problem-solving, analytical, and communication skills.
• Ability to work independently and as part of a collaborative team in a fast-paced environment.

candidate should be strong in Snowflake and ADF
Nice to Have (Added Advantage):

• Experience with dbt (data build tool) for data transformation and modeling. & Knowledge of other programming languages such as Python.
• Familiarity with DevOps practices for data engineering (CI/CD).