Job Description

Strong hands-on experience in Python programming, including Pandas, NumPy, and data processing libraries.
Strong experience with PySpark for distributed data processing and large-scale data transformation.
Extensive knowledge of SQL, including complex queries, joins, CTEs, window functions, and query optimization.
Hands-on experience in ETL/ELT development, data integration, data migration, and pipeline orchestration.
Strong experience with Snowflake, including Snowflake SQL, virtual warehouses, stages, streams, tasks, and Snowpipe.
Good understanding of relational databases such as SQL Server, Oracle, PostgreSQL, or MySQL.
Experience in data warehousing concepts, dimensional modeling, fact and dimension tables, and schema design.
Understanding of batch processing, incremental loads, data validation, and error handling.
Experience with Git, version control, debugging, and code