Cloud Data Engineer

Cloud Data Engineer

Cloud Data Engineer with over 5 years of experience in managing structured and unstructured data, performing deep data analysis, and building scalable data pipelines. The ideal candidate will have hands-on expertise in Azure Data Factory (ADF), Snowflake, Databricks, and Python/PySpark, with a strong understanding of cloud-based ETL processes and data normalization techniques.

Minimum of 5+ years of experience as a Cloud Data Engineer. Hands-on experience with Azure Cloud data tools (ADF, Logic Apps, ADLS Gen2, Blob Storage) and Snowflake. Strong experience in ETL development using SQLServer, SSIS, and T-SQL.

Key Responsibilities:

• Analyze and organize raw data from diverse sources, including healthcare datasets.
• Design and implement ETL pipelines using Azure Data Factory.
• Develop and optimize SQL queries, stored procedures, and data models in Snowflake.
• Parse and flatten semi-structured data (XML, JSON) using Snowflake and SQL.
• Build scalable data systems and pipelines to support analytics and reporting.
• Migrate on-premise data workloads to cloud platforms, preferably Snowflake.
• Work with Databricks using PySpark, SparkSQL, and Python for data transformation.
• Ensure data quality through profiling, validation, and adherence to governance standards.
• Collaborate in Agile development environments and contribute to continuous improvement.
• Identify opportunities to enhance data architecture and storage efficiency.