Snowflake is growing fast and we’re scaling our team to help enable and accelerate our growth. We’re passionate about our people, our customers, our values and our culture! We’re also looking for people with a growth mindset and the pragmatic insight to solve for today while building for the future. And as a Snowflake employee, you will be accountable for supporting and enabling diversity and belonging. Snowflake started with a clear vision: make modern data warehousing effective, affordable, and accessible to all data users. Because traditional on-premises and cloud solutions struggle with this, Snowflake developed an innovative product with a new built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions.
AS A SECURITY ANALYTICS TECH LEAD AT SNOWFLAKE YOU WILL:
- Take charge and ownership of security data, and drive strategy and implementation, ensuring data integrity, quality and availability long term.
- Interface with stakeholders to understand data needs, and build data products that inform our Security and Compliance decisions, alerting, and strategy.
- Mentor and guide junior data scientists.
OUR IDEAL SECURITY ANALYTICS TECH LEAD WILL HAVE:
- Passion for mentoring with the ability to deliver constructive feedback to bring out the best in a team and help direct reports grow in their careers
- Experience in the design, implementation and maintenance of internal data ecosystem and ingestion and analysis pipelines
- Experience with data ingestion code, pipelines, and maintenance
- Experience working with large-scale data warehousing and analytics projects, including using AWS technologies – Redshift, S3, EC2, Data-pipeline and other big data technologies.
- Extensive knowledge of data science pipeline architecture, machine learning environments, and latest developments in the field.
- Experience with all steps of the modeling process from ideation to productionalizing code, including ongoing data quality verification.
MUST HAVE 7 YEARS WITH THE FOLLOWING REQUIREMENTS:
- quantitative analysis or statistical modeling
- schema design and dimensional data modeling
- custom ETL design, implementation and maintenance
- data quality implementation and assurance, and all related technologies
- one or more of: Python, R, Julia, Scala for data science, and SQL
- analyzing data to identify deliverables, gaps and inconsistencies, and resolving these on an ongoing basis
BONUS POINTS FOR EXPERIENCE WITH THE FOLLOWING:
- Machine Learning experience