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In this role, you will:
Collaborate with team members and business partners to collect business requirements, define successful analytics outcomes, and design data models.
Build trust in all interactions, working backwards from a business impacting outcome, utilizing Agile data-product development.
Design, develop, and extend code repository to extend the Enterprise Dimensional Model (Co-owned by Data-engineering, BI and Go-To-Market Analytics).
Maintain the Rapid7 Data Catalog, a scalable resource to support Self-Service and Single-source-of-truth analytics for business partners.
Document plans and results in user-stories, issues, Confluence pages - following the tradition of documentation first!
Craft code that meets our internal standards for style, maintainability, and best practices (such as the ) for a high-scale database environment. Maintain and advocate for these standards through code review.
Approve data model changes as a Data Team Reviewer and code owner for specific database and data model schemas.
Provide data modeling expertise to all Rapid7 teams through code reviews, pairing, and training to help deliver optimal, DRY, and scalable database designs and queries in Snowflake and in Tableau.
Play a vital role in building the infrastructure for identifying strategic data opportunities for the business by highlighting / investigating areas of opportunity for all data consumers within Rapid7.
Assist with onboarding users and other administration tasks in DBT and Tableau
Assist with enablement efforts for dbt and Tableau to support analysts across Rapid7
The skills you’ll bring include:
Ability to thrive in a hybrid organization.
“Be an advocate” for data-driven decision making in our cross-functional teams (Data Engineering, BI-Finance, Product Analytics).
Positive and solution-oriented mindset.
Comfort working in an agile, iterative environment.
Self-motivated and self-managing, with a high level of organizational skills.
Great communication: Regularly achieve consensus amongst technical and business teams.
Demonstrated capacity to clearly and concisely communicate complex business activities, technical requirements, and recommendations.
Demonstrated experience providing technical leadership & data design.
Have a solid understanding of data warehouses, business intelligence tools, and the Modern Data Stack.
Proficiency in engineering best practices (sprints, code reviews, etc.)
1+ year(s) in dbt. This means you consider yourself well-versed in dbt modeling and understand how to build modular, performant models.
4+ years in the Data space as an analyst, data-scientist, data-engineer, or equivalent.
2+ years experience designing, implementing, operating, and extending enterprise dimensional data models.
2+ years experience building reports and dashboards in a data visualization tool.
GitHub experience preferred
Python experience preferred (For use with DBT & airflow)
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