Senior Snowflake Engineer

Key Responsibilities

• Design, develop, and manage Snowflake data warehouse solutions.
• Establish best practices for Snowflake usage with tools like Airflow, DBT, and Spark.
• Develop and deploy data pipeline frameworks using CI/CD and standard testing tools.
• Monitor and tune query and data load performance.
• Support QA and UAT phases by validating issues and identifying root causes.
• Integrate Snowflake with internal platforms for data quality, cataloging, discovery, incident logging, and metrics.
• Utilize Snowflake features such as data sharing, time travel, Snowpark, and workload optimization.
• Ingest and manage structured and unstructured data across hybrid environments.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or related field.
• Minimum 10 years of experience in data development in complex, high-volume environments.
• At least 7 years of experience with SQL/PLSQL and complex query development.
• Minimum 5 years of experience developing data solutions on Snowflake.
• At least 3 years of experience with Python and libraries such as Pandas, NumPy, PySpark.
• At least 3 years of experience in hybrid data environments (on-prem and cloud).
• Hands-on experience with Airflow (or similar tools like Dagster).
• Snowflake SnowPro Core certification (mandatory).

Preferred Qualifications

• Snowflake SnowPro Advanced Architect and Advanced Data Engineer certifications.
• Experience with DBT.
• Strong skills in performance tuning of SQL queries, Spark jobs, and stored procedures.
• Understanding of E-R data models and advanced data warehouse concepts (e.g., Factless Fact Tables, Temporal/Bi-Temporal models).
• Experience in functional and event-driven programming.
• Familiarity with AWS, Kubernetes, and Docker.
• Strong analytical and problem-solving skills