snowflake Data Engineer

Mandatory Skills (Primary):

• 5+ years of professional Python development with a focus on core principles and software best practices.
• Streamlit & Snowpark: Proven experience building data applications and leveraging Snowpark for Python-based data processing.
• Web Frameworks: Expertise in FastAPI, Flask, or Django for building scalable backends.
• DevOps: Strong command of Git and CI/CD pipelines to ensure independent, production-ready delivery.
• Testing: Proficiency in unit and integration testing to ensure application stability.

Secondary Skills (Moderate Proficiency):

• Snowflake: Comfortable navigating Snowflake, managing stages, and understanding virtual warehouses.
• SQL & DBT: Ability to write clean SQL and manage basic data transformations using DBT.
• Data Modeling: Basic understanding of data structures to facilitate reporting and analytics.

Key Responsibilities

• Application Development: Architect and build interactive data applications using Streamlit, ensuring a seamless user experience for internal stakeholders.
• Data Processing with Snowpark: Use Snowpark to shift data processing logic from traditional SQL into Python, allowing for more complex and maintainable codebases.
• End-to-End Automation: Utilize Python to automate manual data processes, from ingestion to visualization.
• Collaborative Agile Delivery: Work within an Agile framework (Scrum) to deliver features independently while staying aligned with BA and QA requirements.
• Performance Tuning: Optimize Python code and Streamlit app performance to handle large datasets efficiently.

Analytical & Communication Skills

• Problem Solving: Ability to translate complex business logic into clean, functional Python code.
• Communication: Ability to explain technical application architecture to team members and present data insights in an understandable way.