Lead Snowflake Data Engineer

About the Role

EPAM Systems seeks a seasoned Lead Snowflake Data Engineer to join its data engineering division. The successful candidate will spearhead the design, creation, and upkeep of scalable data architectures on Snowflake's cloud data platform. This position demands deep knowledge of contemporary data engineering, cloud infrastructure, and integration of AI/ML capabilities within Snowflake.

Key Responsibilities

• Architect and deploy reliable data pipelines utilizing Snowflake's built-in functionalities.
• Write and fine-tune complex data queries using Snow SQL and Snow PLSQL.
• Create scalable data applications leveraging the Snowpark framework and Python.
• Oversee Snowflake environments deployed on AWS and Azure platforms.
• Integrate Snowflake with diverse cloud services, multiple data sources, and governance standards.
• Manage cloud resources efficiently with a focus on cost optimization.
• Handle data workflows using Apache Airflow and DBT for orchestration and transformations.
• Guarantee the quality, dependability, and performance of data pipelines.
• Diagnose and resolve issues in data pipelines promptly.
• Utilize Snowflake Cortex AI to advance analytics and machine learning initiatives.
• Partner with data scientists to deploy ML models at scale within Snowflake environments.

Candidate Requirements

• Between 8 and 15 years of experience in data engineering, emphasizing cloud data platforms.
• At least 4 years of practical experience specifically with Snowflake, including using Snow SQL, Snow PLSQL, and the Snowpark framework.
• Strong Python programming skills applied to data engineering tasks.
• Competency with cloud services, particularly AWS and/or Microsoft Azure.
• Experience working with Apache Airflow and DBT for workflow orchestration and data modeling.
• Knowledge of Snowflake Cortex AI's integrated AI and ML features.

Eligibility

Applications are welcomed from any graduate.