Snowflake platform engineer

• Evaluate Snowflake for data processing, storage, and analytics while considering key factors such as security, scalability, performance, and cost.
• Establish and enforce data engineering best practices, standards, and guidelines to ensure data quality, reliability, and consistency in terms of Snowflake.
• Research, test, benchmark, and assess new Snowflake features, providing recommendations for their integration into the data platform.
• Develop and implement Snowflake-based solutions that align with business strategy, architectural considerations, and both short- and long-term roadmaps, ensuring high scalability and extensibility.
• Optimize Snowflake performance, conduct tuning, and troubleshoot data infrastructure components to maximize efficiency and resource utilization.
• Proactively identify bottlenecks , gaps, and opportunities, in snowflake and driving necessary changes through direct action or by influencing peers and leadership.
• Deploy Snowflake following best practices, ensuring knowledge transfer so engineers can independently extend its capabilities.
• Engage hands-on with customers to demonstrate and communicate Snowflake implementation best practices.
• Support prospects and customers throughout the sales cycle, from demos to proof-of-concept, design, and implementation, effectively showcasing Snowflake’s value.
• Collaborate with Product Management, Engineering, and Market teams to continuously enhance Snowflake’s solutions.
• Apply hands-on expertise with AWS and cloud-based data services such as Snowflake.
• Leverage software engineering and analytical skills to solve large-scale business challenges.
• Utilize modern data pipeline, replication, and processing tools such as Matillion, Fivetran, DBT, Airflow, and Astronomer.
• Ensure compliance with data security and privacy regulations, implementing best practices for data protection.
• Understand the end-to-end data analytics stack and workflow, from ETL processes to data platform design and BI tools.
• Demonstrate expertise in large-scale databases, data warehouses, ETL, and cloud technologies, including Data Lakes, Data Mesh, and Data Fabric.
• Bridge the gap between business challenges and Snowflake’s solutions, aligning data architecture with customer needs.
• Conduct deep discovery of customer architecture frameworks and integrate them with Snowflake’s data architecture.
• Exhibit strong proficiency in databases, data warehouses, and data processing to drive effective decision-making.
• Demonstrate advanced SQL and SQL analytics expertise with extensive hands-on experience.
• Define and manage user roles and permissions in Snowflake to maintain data security and privacy.
• Utilize version control systems such as Git and implement CI/CD workflows.
• Deliver compelling presentations to both technical and executive audiences, using whiteboards, slides, and demos to effectively communicate complex concepts.

Provide architectural expertise in data engineering, confidently engaging with business executives and technical teams while handling impromptu questions.