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Analytics Engineer

San Francisco

why we're looking for you

Retool has set out to radically rethink how this custom internal software is built. We’ve created a new type of development environment, combining visual, drag-and-drop manipulation with code-based customization. It seamlessly integrates with nearly any data source and enables instant deployment to end-users. It’s a force multiplier for developers building internal tools, dramatically faster and easier than writing software from scratch.

We’ve made great progress so far: today, thousands of companies use Retool to create the internal software that powers their businesses, from small startups to Fortune 500 companies. We’re growing quickly and have assembled an incredible set of investors, including Sequoia and the founders of GitHub, Stripe, Plaid, Gusto, PagerDuty, Segment, and Y Combinator.

Retool is a fast growing company with quickly evolving business needs. We’re looking to hire our first Analytics Engineer to help us build out our analytics and business intelligence systems to serve the needs of our business today, and for broader scale years from now. We're looking for someone who is ready to get their hands dirty, is motivated by having an impact on the business, and is constantly curious.  This is the right role for someone who thrives while making sense of the blurry space that is data at a high growth startup.

what you'll do

As our first Analytics Engineer, you will build a foundation that strengthens Retool’s data culture at scale. You’ll initiate projects that solidify Retool’s reporting capabilities and help the company remain data-driven. Our data team is in its early stages, so you will have the opportunity to help define our data team structure and operating rhythm for the future. You’ll develop data sets to streamline operations, inform strategic priorities, and develop product insights. We’ll look to you to define key metrics and develop dashboards that empower stakeholders to make data-informed decisions. You’ll also take on ownership of our data stack to ensure that your teammates are able to access the data they need to make decisions and technical teams are able to quickly implement events. We’ve already built out a solid stack on top of Segment, BigQuery, DBT, and of course, Retool, but we need your help to ensure it scales with the company as our user base grows.

who you'll work with

As part of our data team you’ll work with stakeholders across the business, including finance, marketing, engineering, product, operations, and support. You’ll be joining a broader team of Retools who are passionate about serving our customers, enjoy collaborating to build an incredibly innovative product, and enjoy swapping stories. If this sounds like you, we’d love to hear from you!

in this role, you'll:

  • Partner with business teams to deploy robust reports and analyses, surfacing key insights that shape Retool’s future direction
  • Develop dashboards and define metrics that drive key business decisions 
  • Build and maintain scalable ETL pipelines
  • Design our Analytics and Business Intelligence architecture, assessing and implementing new technologies where fitting
  • Work with our engineering teams to ensure robust instrumentation across areas of the product

the skillset you'll bring:

  • Background in Analytics Engineering, Business Intelligence, Data Engineering, or Data Analytics.
  • Ideally 3+ years of experience managing and building large complex data sets across a range of sources.
  • Experience implementing and defining best data practices at scale.
  • Strong SQL and data modeling skills, with experience applying skills to thoughtfully create data models in a warehouse environment.
  • Excellent business acumen with the ability to translate stakeholder requirements into data models.
  • Hand-on knowledge of ETL and data warehouse technologies (i.e. dbt, BigQuery, Redshift,  Airflow, Snowflake).
  • Skilled at data visualization, with strong opinions on the right way to distill information to various audiences.
  • Comfortable with common git workflows and at least one scripting or statistical programming language (ideally Python and/or R).
  • A solution-oriented growth mindset. You’ll need to be a self-starter and thrive in a dynamic environment.
  • A bias towards communication and collaboration with business and technical stakeholders. 
  • Quantitative rigor and systems thinking.
  • Prior startup experience preferred, but not required.