Responsibilities
- Create and manage scalable ETL and ELT workflows to bring data from diverse sources into Snowflake.
- Build and optimize data warehouse components such as databases, tables, views, and materialized views in Snowflake.
- Develop data transformation processes using SQL, dbt, Python, or equivalent tools within Snowflake-based environments.
- Tune Snowflake virtual warehouses to balance performance, concurrency, and cost.
- Leverage Snowflake capabilities like stages, tasks, streams, time travel, zero-copy cloning, and secure data sharing as needed.
- Process and load both structured and semi-structured data formats such as JSON, Avro, and Parquet.
- Analyze and improve query performance, resolve failures, and optimize workloads for stability and scale.
- Establish data validation rules, quality checks, and monitoring systems for production data pipelines.
- Collaborate with analysts, BI teams, architects, and business partners to convert data needs into technical implementations.
- Enforce data governance, security policies, role-based access, and regulatory compliance in Snowflake.
- Support continuous integration and deployment practices for data workflows and automation.
- Document technical designs, data models, Snowflake objects, and operational procedures.
