Sr. Snowflake Data Engineer

Job Description:
Skills:

1. Snowflake, DBT, Python
2. Experience level : 5-7 years of relevant experience
3. Insurance industry data sets knowledge and work experience needed.

A Snowflake Data Engineer is responsible for designing, implementing, and optimizing data pipelines, storage solutions, and databases within the Snowflake platform, including tasks like data modeling, ETL process management, writing optimized SQL queries, ensuring data security, integrating Snowflake with other tools, and collaborating with cross-functional teams to support data-driven decision making; essentially acting as a specialist in building and maintaining robust data infrastructure on the Snowflake cloud platform.
A Snowflake Data Engineer is responsible for designing, implementing, and optimizing data pipelines, storage solutions, and databases within the Snowflake platform, including tasks like data modeling, ETL process management, writing optimized SQL queries, ensuring data security, integrating Snowflake with other tools, and collaborating with cross-functional teams to support data-driven decision making; essentially acting as a specialist in building and maintaining robust data infrastructure on the Snowflake cloud platform.

Key responsibilities of a Snowflake Data Engineer:

• Data pipeline design and development: Create and manage data pipelines to ingest, transform, and load data into Snowflake from various sources, optimizing for performance and scalability.
• Data modeling: Design and implement efficient data models within Snowflake, considering data access patterns and business requirements.
• SQL query optimization: Write and optimize complex SQL queries to efficiently retrieve data from Snowflake.
• Performance tuning: Analyze and troubleshoot performance bottlenecks in Snowflake queries and data pipelines.
• Data integration: Integrate Snowflake with other systems and applications using APIs and connectors.
• Security and compliance: Implement data security measures within Snowflake, ensuring compliance with relevant regulations.
• Monitoring and alerting: Set up monitoring systems to track data pipeline health and performance, creating alerts for potential issues.
• Collaboration: Work with data analysts, data scientists, and business stakeholders to understand data needs and translate them into technical solutions.

Required skills for a Snowflake Data Engineer:

• Proficient in SQL: Strong knowledge of SQL query writing, optimization techniques, and complex data manipulation.
• Snowflake platform expertise: Deep understanding of Snowflake features like data warehousing, data sharing, time travel, and virtual warehouses.
• Data engineering principles: Familiarity with data pipeline design, ETL/ELT processes, data quality checks, and data governance practices.
• Cloud computing knowledge: Understanding of cloud infrastructure (AWS, Azure, GCP) and how to leverage cloud services with Snowflake.
• Programming languages: Proficiency in Python or other scripting languages for data processing and automation tasks.
• Data modeling skills: Ability to design efficient data models for optimal query performance.