Senior Data Engineer - Snowflake Developer

Key Responsibilities

• Design, develop, and optimize ETL/ELT pipelines using Snowflake, SQL, and PySpark to support analytics and reporting needs.
• Write complex, high-performance SQL queries and stored procedures; tune queries and warehouse configurations for cost and performance efficiency.
• Develop and maintain SnowSQL scripts for data loading, transformation, automation, and orchestration within the Snowflake environment.
• Build and manage data ingestion pipelines using Python and PySpark for large-scale structured and unstructured data processing.
• Implement data modeling, schema design, and data quality/validation frameworks within Snowflake.
• Manage Snowflake objects such as warehouses, databases, schemas, roles, and access controls, following best practices for security and governance.
• Troubleshoot and resolve performance bottlenecks, data pipeline failures, and data quality issues.
• Collaborate with business analysts, data scientists, and other engineering teams to understand requirements and translate them into robust technical solutions.
• Document technical designs, data flows, and standard operating procedures clearly for team and stakeholder use.
• Actively use AI-assisted tools (e.g., Copilot, ChatGPT, Claude, or similar) to accelerate coding, debugging, documentation, and query optimization tasks.
• Mentor junior engineers and contribute to establishing engineering best practices within the team.

Required Skills

• Strong proficiency in SQL, including complex joins, window functions, query optimization, and performance tuning.
• Solid working knowledge of Python, particularly PySpark, for data processing and transformation at scale.
• Strong Snowflake development experience, including SnowSQL, Snowpipe, Streams, Tasks, and Snowflakes role-based access control model.
• Experience designing and implementing data warehouse/data lake architectures on Snowflake.
• Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Demonstrated ability to effectively use AI/GenAI tools to improve productivity in coding, testing, and documentation.
• Familiarity with version control (Git) and CI/CD practices for data pipelines.

Good to Have

• Experience with orchestration tools such as Airflow, dbt, or Azure Data Factory.
• Exposure to cloud platforms (AWS, Azure, or GCP) alongside Snowflake.
• Knowledge of data governance, security, and compliance frameworks.
• Prior experience working in Agile/Scrum delivery environments.

Education : Bachelors degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent practical experience).

Education : Bachelors degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent practical experience).

Key Responsibilities

• Design, develop, and optimize ETL/ELT pipelines using Snowflake, SQL, and PySpark to support analytics and reporting needs.
• Write complex, high-performance SQL queries and stored procedures; tune queries and warehouse configurations for cost and performance efficiency.
• Develop and maintain SnowSQL scripts for data loading, transformation, automation, and orchestration within the Snowflake environment.
• Build and manage data ingestion pipelines using Python and PySpark for large-scale structured and unstructured data processing.
• Implement data modeling, schema design, and data quality/validation frameworks within Snowflake.
• Manage Snowflake objects such as warehouses, databases, schemas, roles, and access controls, following best practices for security and governance.
• Troubleshoot and resolve performance bottlenecks, data pipeline failures, and data quality issues.
• Collaborate with business analysts, data scientists, and other engineering teams to understand requirements and translate them into robust technical solutions.
• Document technical designs, data flows, and standard operating procedures clearly for team and stakeholder use.
• Actively use AI-assisted tools (e.g., Copilot, ChatGPT, Claude, or similar) to accelerate coding, debugging, documentation, and query optimization tasks.
• Mentor junior engineers and contribute to establishing engineering best practices within the team.

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