Description

You will design, develop, and maintain ETL/ELT data pipelines using AWS, Snowflake, Databricks, and Spark. You own data transformation workflows with DBT and ensure data quality, governance, and performance tuning.

This role is hybrid.

Responsibilities

• Build scalable data solutions and ETL pipelines using AWS services, Snowflake, and Spark-based frameworks.
• Develop and manage data transformation workflows using DBT and write efficient code in Python and SQL.
• Perform data modelling, warehousing, and performance optimization for cost-efficiency and scalability.
• Collaborate with data analysts and scientists to deliver insights while maintaining data quality standards.
• Ensure robust data governance and validation processes are integrated into the pipeline.

Required Skills

• 7+ years of experience in data engineering.
• Proficiency in Snowflake and DBT for data warehousing and transformation.
• Experience with Databricks and Spark-based processing frameworks.
• Strong programming skills in Python and SQL.
• Hands-on experience with AWS data services.
• Solid understanding of ETL/ELT design patterns and data modelling.
• Ability to optimize pipelines for performance and cost.

Preferred Skills

• Bachelor's degree in Computer Science or related field.

Key Skills

Education

Bachelor's degree