Description

You will design and implement data pipelines and transformation workflows within an Azure and Snowflake ecosystem.

Responsibilities

• Build and maintain ETL/ELT processes and data orchestration workflows using Azure and DBT.
• Develop data transformation logic and models using SQL, Python, and Scala.
• Manage data warehousing tasks in Snowflake, including schema design and performance tuning.
• Execute large-scale data processing tasks using Apache Spark within Databricks.
• Implement data governance and security practices for cloud data architectures.

Required Skills

• 5+ years of experience in data engineering roles.
• Expertise in Snowflake for data warehousing and optimization.
• Strong experience with Azure services including Data Factory, Databricks, and Data Lake.
• Proficiency in DBT for implementing transformation workflows and SQL-based scripting.
• Advanced SQL skills and programming experience in Python and Scala.
• Hands-on experience with Apache Spark and Databricks.
• Experience with Git version control and working in Agile environments.
• Bachelor’s degree in Computer Science, Engineering, Information Technology, or equivalent experience.

Preferred Skills

• DBT certifications or experience with DBT testing, macros, and hooks.
• Azure, Databricks, or Snowflake certifications.
• Experience with Snowflake performance tuning, query optimization, and data partitioning.
• Familiarity with CI/CD practices and automated data pipelines.
• Knowledge of cloud cost optimization in Azure and Snowflake.

Key Skills

Education

Bachelor’s degree in Computer Science, Engineering, Information Technology