Data Engineer - ETL / Python

Essential Duties & Responsibilities :

• Design, develop, and optimize scalable data pipelines for ETL / ELT processes.
• Develop and maintain Python-based data processing scripts and automation tools.
• Write and optimize complex SQL queries (preferably in Snowflake) for data transformation and analytics.
• Work with Jenkins or other CI / CD tools to automate workflows.
• Develop and maintain solutions using Snowflake as the primary data platform.
• Work with ETL / ELT tools (preferably Fivetran, dbt) to manage data workflows.
• Implement version control best practices using Git or other tools to manage code changes.
• Collaborate with cross-functional teams (analysts, product managers, and engineers) to translate business needs into technical data solutions.
• Ensure data integrity, security, and governance across multiple data sources.
• Optimize query performance and database architecture for efficiency and scalability.
• Lead troubleshooting and debugging efforts for data-related issues.
• Document data workflows, architectures, and best practices to ensure maintainability and knowledge Experience & Skills :
• 7+ years of experience in Data Engineering, Software Engineering, or a related field.
• High proficiency in SQL (preferably Snowflake) for data modeling, performance tuning, and optimization.
• Strong expertise in Python for data processing and automation.
• Experience with Git or other version control tools in a collaborative development environment.
• Strong communication skills and ability to collaborate with cross-functional teams for requirements gathering and solution design.
• Experience working with large-scale, distributed data systems and cloud data Experience & Skills :
• Knowledge of cloud platforms (AWS, GCP, Azure) and related services (e.g., S3, Lambda, BigQuery).
• Experience developing Flask-based web applications to create lightweight data-driven tools.
• Familiarity with data governance, security, and compliance best practices.
• Understanding of data modeling principles and database design.
• Experience with containerization (Docker, Kubernetes) and CI / CD pipelines for data engineering

workflows.

(ref : hirist.tech)