Skip to content

Staff Analytics Engineer

Quo LogoQuo
View Organization

Salary

SF Bay Area, Los Angeles, Seattle, Portland, Boston, New York, and Washington, DC Metro: $195,000 - $217,000 USD; All other US Locations: $174,000 - $193,000 USD; Canada: $198,000 - $220,000 CAD

Location

Remote - United States & Canada

As a Staff Analytics Engineer, you will be an early member of the Data & Analytics team, building the foundation to scale analytics across our organization. You will collaborate with key stakeholders in Product, GTM, Finance, Support and other areas to build scalable solutions to transform data into key metrics, reporting, and insights. You will be responsible for ensuring teams have access to reliable, accurate metrics that can scale with our company’s growth. You will also lead your own projects to enable self-serve insights to help teams make data-driven decisions.

Some of the things you’ll do:

  • Translate stakeholder needs into scalable data models and reporting requirements
  • Define, build, and manage key data pipelines in dbt that transform raw logs into canonical datasets
  • Establish and uphold high data integrity standards and SLAs to ensure timely, accurate delivery
  • Develop insightful and reliable dashboards to track the performance of core metrics that will deliver insights to the whole company
  • Build foundational data products and tools that empower teams to self-serve and explore data independently
  • Influence the future roadmap of cross functional teams from a data systems perspective
  • Become an expert in our organization’s data models and the company's data architecture

About you:

  • 8+ years of experience as an Analytics Engineer or similar Data Science & Analytics roles.
  • A passion for Quo's mission to give small businesses modern, intuitive tools to connect with customers quickly, build trust, and create lasting relationships
  • Expertise in building multi-step ETL jobs through tooling like dbt; proficiency with workflow management platforms like Airflow and version control management tools through GitHub.
  • Expertise in SQL and Python to transform data into accurate, clean data models
  • Experience designing dashboards and visualizations in tools like Hex, empowering multiple teams with actionable insights
  • A bias for action and urgency, not letting perfect be the enemy of the effective.
  • A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.
  • Experience building an Analytics Engineering (or similar) function at start-ups.
  • A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.
  • Bonus: familiarity with AWS (EC2, S3) and modern data stack best practices

‌