Description

You will design, develop, and maintain scalable data pipelines that ingest, transform, and load data into the Snowflake Data Cloud.

This role is hybrid.

Responsibilities

• Build and optimize ETL/ELT pipelines using Python and Snowflake SQL to load data from databases, APIs, flat files, and cloud storage (S3, Azure Blob, GCS).
• Implement data transformations using Snowpark and ensure data quality through validation and reconciliation processes.
• Orchestrate workflows using Airflow, Azure Data Factory, dbt, or Control-M, and manage deployments via CI/CD pipelines.
• Optimize Snowflake performance through clustering, partitioning, caching, and warehouse sizing.
• Ensure data security and governance using RBAC, masking policies, and encryption while troubleshooting job failures.

Required Skills

• 5+ years of experience with Snowflake Data Cloud and strong proficiency in Python for ETL (Pandas, PySpark, Snowpark).
• Strong SQL skills, specifically within the Snowflake environment.
• Experience with ETL/ELT tools and orchestration frameworks such as Airflow, Azure Data Factory, dbt, or Control-M.
• Knowledge of cloud platforms including AWS, Azure, or Google Cloud Platform.
• Experience with data modeling, including star and snowflake schemas.
• Familiarity with CI/CD, Git, and DevOps practices.
• Understanding of data security, governance, and compliance standards.

Preferred Skills

• Experience building reusable Python modules and frameworks for ETL automation.
• Background in collaborating with analytics, BI, and data science teams to support reporting.

Key Skills

Education

Any Graduate