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Responsibilities:
Design, develop, and optimize Snowflake data warehouse solutions to meet business requirements.
Collaborate with stakeholders to gather and understand data requirements, and translate them into technical specifications.
Perform data modeling and schema design to ensure efficient and scalable data storage and retrieval.
Develop and maintain ETL processes using Snowflake's features and capabilities, such as stored procedures, tasks, and streams.
Implement data integration pipelines to ingest data from various sources into Snowflake, ensuring data quality and integrity.
Optimize queries and data processing for performance and scalability, utilizing Snowflake's indexing, clustering, and partitioning techniques.
Troubleshoot and resolve data-related issues, including data quality, data transformation, and performance bottlenecks.
Collaborate with cross-functional teams, including data engineers, data analysts, and business stakeholders, to deliver high-quality data solutions.
Stay up-to-date with the latest Snowflake features and best practices, and evaluate their applicability to enhance existing systems.
Requirements:
Must have 6+ yrs. experience in Snowflake, ETL tools like Informatica, DMX and Data analysiso Must have 3+ yrs. experience in Pythono Hands on exposure into Unix, Unix shell Scripting
o Must have hands on experience in Oracle, SQL, PostgreSQL, Snowflake.o Must have hands on Data Warehousing o Experience in Hadoop, Sqoop, Hive will be added advantage. o Good to have experience in AWS cloud stack with experience in Aws S3 Athena preferred. o Must understand any scheduling tools like, A utosys, Control-M, Tivoli etc o Should be able to handle client independently, take up requirements and suggest solution whenever required
Preferred Skills:
Snowflake certification(s).
Experience with data visualization tools, such as Tableau or Power BI.
Knowledge of scripting languages like Python or Shell scripting.
Familiarity with data governance and data security practices.
