Data Engineer

Required :
8+ 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.