This is a remote position.
Design, develop, and maintain Snowflake-based data warehouse solutions.
Build scalable ELT/ETL pipelines using Snowflake-native capabilities and tools like DBT.
Implement data ingestion frameworks for structured and semi-structured data (JSON, Parquet, Avro).
Optimize Snowflake performance using warehouse sizing, multi-cluster configurations, partitioning, clustering, and query tuning.
Drive cost optimization and usage monitoring within Snowflake environments.
Integrate Snowflake with cloud platforms (AWS S3, Glue, or Azure services).
Develop event-driven ingestion patterns for real-time data processing.
Build data validation, reconciliation, and monitoring frameworks to ensure data quality.
7+ years of overall experience in data engineering.
3+ years of hands-on experience with Snowflake development.
Strong experience working with Snowflake on AWS or Azure.
Advanced proficiency in SQL, including performance tuning.
Experience with Python or Scala for data processing.
Solid understanding of data warehousing concepts and ELT/ETL design patterns.
Strong knowledge of distributed data processing frameworks.
Experience with streaming technologies such as Kafka or Azure Event Hubs.
Exposure to DBT or similar modern data transformation tools.
Experience designing event-driven and real-time data pipelines.
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management skills.

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