Snowflake开发工程师

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, Autosys, 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.

Originally posted on Himalayas