Description
Job Description:
• 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.
• 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.