Data Engineer

Required :
10+ Years of hands on experience on below skillset
1. Snowflake
2. Azure Databricks
3. Azure Data Factory
4. Pyspark
5. Python
6. SQL

Role and Responsibilities:
Design, implement, and manage Azure cloud solutions for various projects.
• Develop and maintain data pipelines using Databricks (PySpark) for data ingestion, processing, and analysis.
• Configure and manage Azure Data Factory (ADF) to orchestrate data workflows and ETL processes.
• Implement and optimize Azure Data Lake Storage (ADLS) for efficient data storage and retrieval.
• Collaborate with cross-functional teams to design and implement data warehouse solutions.
• Utilize Git for version control and collaboration on codebase.
• Monitor, troubleshoot, and optimize data processes for performance and reliability.
• Implement security best practices and manage access controls using Azure Active Directory (AAD).
• Document technical designs, processes, and procedures.
• Stay updated with the latest Azure cloud technologies and best practices.
Requirements:
• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience working with Azure cloud services, including Azure Data Lake Storage, Azure Data Factory, and Azure Active Directory.
• Strong proficiency in PySpark and experience with Databricks for data engineering and analytics.
• Hands-on experience with Git for version control and collaboration.
• Familiarity with data warehousing concepts and technologies.
• Experience with SQL and relational databases.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.
• Ability to work effectively in a fast-paced, dynamic environment.
• Azure certifications (e.g., Azure Administrator, Azure Data Engineer) are a plus