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Analytics Engineers sit at the intersection of business teams, Data Analytics and Data Engineering and are responsible for bringing robust, efficient, and integrated data models and products to life. Analytics Engineers speak the language of business teams and technical teams, able to translate data insights and analysis needs into models powered by the Enterprise Data Cloud - Snowflake. The successful Analytics Engineer is able to blend business acumen with technical expertise and transition between business strategy and data development.
Responsibilities:
As a key leader responsible for helping to bridge the gap between business and technology, in-service of data-driven business growth and operation the Analytics Engineer role requires equal amounts of business acumen and technical acumen.
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.
Serve as the Directly Responsible Individual for major sections of the Enterprise Dimensional Model.
Design, develop, and extend dbt code repository to extend the Enterprise Dimensional Model (Co-owned by Data-engineering, BI and Go-To-Market Analytics).
Create and maintain architecture and systems documentation in the “Data Team” Handbook.
Maintain the Go-To-Market 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, MRs, the team's handbook - following the tradition of documentation first!
Implement the DataOps philosophy in everything you do.
Craft code that meets our internal standards for style, maintainability, and best practices (such as the SQL Style Guide) 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 our go-to-market customer experiences.
Requirements:
Ability to thrive in a hybrid organization.
“Be an advocate” for data-driven decision making, and management in the Go-To-Market organization as-well as for the Go-To-Market perspective in the cross-functional data-teams (Data Engineering, BI-Finance, Product Analytics).
Positive and solution-oriented mindset.
Comfort working in a highly agile, intensely iterative environment.
Self-motivated and self-managing, with task 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 with the “Sales” domain.
Experience in the following domains will be considered a big advantage: Marketing, Product, Customer success, Customer support.Have a solid understanding of data warehouses, business intelligence tools, data activation tools, and the Modern Data Stack.
1+ year(s) in dbt. This means you consider yourself well-versed in dbt modeling and understand how to build modular, performant models.
5+ 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.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.