We're seeking our first Analytics Engineer. This is an opportunity to help us build out our analytics and BI from the ground up.

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 . The successful Analytics Engineer is able to blend business acumen with technical expertise and transition between business strategy and data development.

Responsibilities

As a team member responsible for helping to bridge the gap between business and technology, the Analytics Engineer role requires equal amounts business acumen and technical acumen.

  • Collaborate with team members to collect business requirements, define successful analytics outcomes, and design data models
  • Build trust in all interactions
  • Serve as the Directly Responsible Individual for all internal analytics
  • Design, develop, and build ETL and data lake
  • Architect and develop a data warehouse solution
  • Create and maintain architecture and systems documentation
  • Create a Data Catalog, a scalable resource to support Self-Service and Single-source-of-truth analytics
  • Document plans and results in either issues, MRs, or wiki
  • Implement the DataOps philosophy in everything you do
  • Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale database environment. Maintain and advocate for these standards through code review.
  • Create and document data models and schemas
  • Provide data modeling expertise to all SalesRabbit teams through code reviews, pairing, and training to help deliver optimal, DRY, and scalable database designs and queries in our data lake and warehouse

Requirements

  • Ability to use GitLab
  • Ability to thrive with little oversight
  • 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 one or more of the following business subject areas: marketing, finance, sales, product, customer success, customer support, engineering, or people
  • 4+ years in the Data space as an analyst, engineer, or equivalent
  • 4+ years working with a large-scale (1B+ Rows) Data Warehouse, preferably in a cloud environment
  • 2+ years experience building reports and dashboards in a data visualization tool
  • 1+ years creating project plans to identify tasks, milestones, and deliverables