Snowflake Developer - ETL/Python

About the Role :

We are seeking an experienced and passionate Snowflake Developer to join our data engineering team. The ideal candidate will have a solid background in data integration, transformation, and cloud data warehousing using Snowflake, along with hands-on experience in Python, SQL, and various data ingestion tools.

As a Snowflake Developer, you will be responsible for developing scalable data pipelines, optimizing data workflows, and supporting various business and analytics teams with data solutions. A strong focus on troubleshooting, automation, and performance tuning is essential.

Key Responsibilities :

- Design, develop, and optimize data pipelines and ETL/ELT workflows using Snowflake.

- Create complex SQL queries, views, and stored procedures to support reporting and analytics needs.

- Develop and maintain Python scripts for data processing, automation, and custom integrations.

- Work with various cloud storage systems such as AWS S3, SFTP, and integrate them into Snowflake pipelines.

- Manage data ingestion from structured and semi-structured sources into Snowflake.

- Implement secure data transfer mechanisms and maintain data lineage and metadata documentation.

- Proactively monitor pipelines, resolve data issues, and troubleshoot system errors using tools like JIRA and Confluence.

- Collaborate with cross-functional teams to understand business requirements and resolve data issues efficiently.

- Perform configuration and connectivity issue resolution for Snowflake and integrated tools.

- Work with JIRA for ticket tracking, Confluence for documentation, and Excel for ad-hoc data manipulations.

- Use IDP (Intelligent Data Processing) or Automic (if experienced) for workflow automation and scheduling.

Required Skills & Qualifications :

- 3+ years of hands-on experience as a Snowflake Developer.

- Strong command of SQL, Python, and Snowflake development.

- Proven experience with stored procedures, UDFs, and data transformation logic in Snowflake.

- Experience with cloud platforms (AWS preferred) and tools like S3, SFTP.

- Familiarity with data pipeline orchestration, job scheduling, and automation frameworks.

- Good understanding of data preparation, data quality, and data governance principles.