Key Responsibilities
- Design, develop, and optimize data pipelines using Snowflake and ETL/ELT frameworks.
- Write complex SQL queries, stored procedures, and performance-optimized transformations.
- Build and maintain scalable data ingestion and transformation workflows.
- Implement data warehouse solutions, data modeling, and data integration processes.
- Work with Python and PySpark for data processing and transformation.
- Optimize Snowflake query performance, warehouse utilization, and compute costs.
- Integrate data from multiple sources, including cloud storage, databases, and APIs.
- Implement data quality checks, error handling, and monitoring.
- Collaborate with data architects, analysts, and business stakeholders.
- Follow best practices for data security, governance, and access management.
Mandatory Skills
- Snowflake: Hands-on experience with Snowflake data warehouse, SQL, and query optimization.
- SQL: Strong experience writing complex queries, joins, CTEs, window functions, and performance tuning.
- ETL/ELT: Experience developing and maintaining data pipelines.
- Python: Data processing, transformation, and automation.
- Data Modeling: Experience with dimensional modeling, schema design, and data warehouse concepts.
- Cloud Data Platforms: Experience with AWS, Azure, or GCP.
Good-to-Have Skills
PySpark / Apache Spark
- Databricks and Delta Lake
- Apache Airflow or other workflow orchestration tools
- Snowflake Streams, Tasks, Snowpipe, and Dynamic Tables
- Snowflake performance tuning and cost optimization
- CI/CD, Git, and automated testing
- Cloud storage and data lake integration
Job description provided by eClerx.
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