Staff Data Engineer

Vanta is a company dedicated to securing the internet and protecting consumer data. They are seeking a Staff Data Engineer to lay the foundation for a best-in-class analytics function, partnering closely with engineering teams and business stakeholders to meet analytics needs and drive data-driven decision-making solutions.

Responsibilities:

• Design and implement complex data models, modeling metadata, building reports and dashboards and creating reporting tools for data science and ML products users
• Design and deploy data infrastructure needed to drive data-driven decision-making solutions
• Be the company’s expert on data administration and master data management
• Be a technical thought leader on the development of scalable data systems
• Develop front end applications to expose analytical data sets enterprise wide
• Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses
• Work with the Product and Enterprise Engineering system teams to structure source systems for reporting consumption across the enterprise
• Help maintain the CDC pipeline to power customer reporting

Requirements:

• Have at least six years of experience working with data and two years of experience in Software Engineering or a related field
• Have experience with common analytics tooling (e.g. Stitch/Fivetran, Snowflake/BigQuery/Redshift, dbt, Airflow, Dagster, Looker/Mode/Sigma)
• Have led an implementation of Debezium or another CDC event tracking system
• Have good working knowledge of AWS data infra systems and Terraform
• Bring a system-oriented and software engineering mindset to the Data Engineering practice. We're looking to build frameworks that manage data, and minimize bespoke queries
• Deep knowledge of crafting dimensional and fact models in modern data fashion (experience at Amazon, Facebook, etc a plus)
• Have a passion for enabling the developer experience of data, and being obsessed with giving data super powers across the company
• Desire to lead the industry in security, anonymization, and compliance management when it comes to data warehousing