Data Engineer

Key Responsibilities:
Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory (ADF).
Implement and optimize data warehousing solutions in Snowflake.
Develop data integration workflows between various sources such as APIs, databases, flat files, and cloud storage.
Perform data transformation using SQL, Snowflake procedures, and other transformation tools.
Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
Implement data security, access control, and governance best practices.
Collaborate with business analysts, data scientists, and application teams to gather requirements.
Create technical documentation, data flow diagrams, and deployment guides.
Support CI/CD processes and DevOps integration for data pipelines.
Ensure data quality, validation, and error-handling mechanisms are in place.

Required Skills & Qualifications:
7+ years of experience in Data Engineering.
Strong hands-on experience with Azure Data Factory (ADF).
Strong experience working with Snowflake (data modeling, performance tuning, clustering, tasks, streams).
Advanced SQL skills.
Experience with Azure ecosystem (Azure Blob Storage, Azure Data Lake, Azure SQL, etc.).
Experience in building and optimizing data warehouses and dimensional data models.
Knowledge of ETL/ELT design patterns and best practices.
Experience with version control (Git) and CI/CD pipelines.
Strong problem-solving and analytical skills.

Preferred Qualifications:
Experience with Azure Databricks or Spark.
Knowledge of Python for data processing.
Experience with Power BI or other BI tools.
Familiarity with data governance and compliance frameworks.
Microsoft Azure or Snowflake certifications.