Analytics Engineer, Data Science

<div class="content-intro"><p><img style="display: none; max-width: 100%;" src="https://click.appcast.io/greenhouse-te8/a31.png?ent=34&amp;e=22630&amp;t=1701374353806" width="1px"> <img style="display: none; max-width: 100%;" src="https://track.jobadx.com/v1/i.gif?utm_pixel=224e990b-8ff4-4287-8d5d-2ff09647f181&amp;utm_ptz=EST&amp;utm_rqt=track" alt="" width="1"></p></div><h2><strong>About the Team</strong></h2> <p>The Analytics Engineering team at DoorDash is embedded within the Analytics and Data Engineering Orgs, and is responsible for building internal data products that scale decision-making across business teams and drive efficiency in our operations. Data is fundamental to DoorDash’s success, and this team plays a critical role in enabling high-impact, data-driven solutions across Product, Operations, Finance, and more.</p> <p><strong>Please apply here for all non-managerial levels within the following analytics teams:</strong></p> <ul> <li>Consumer &amp; Growth</li> <li>Business Operations</li> <li>Dasher &amp; Logistics</li> <li>Customer Experience &amp; Integrity</li> <li>Merchant</li> <li>Ads &amp; Promotions&nbsp;</li> <li>New Verticals</li> </ul> <h2><strong>About the Role</strong></h2> <p>As an Analytics Engineer, you’ll play a key role in building and scaling the data foundations that enable fast, reliable, and actionable insights. You’ll work closely with partner teams to drive end-to-end analytics initiatives, working alongside Data Engineers, Data Scientists, Software Engineers, Product Managers, and Operators.</p> <p>This is a highly technical role where you'll be a driving force behind the analytics stack, delivering trusted data and metrics that support decision-making at all levels of the company. If you're energized by solving technical problems with data and are comfortable being deeply embedded across several domains, this role is for you!</p> <h2><strong>You're excited about this opportunity because you will…</strong></h2> <ul> <li>Collaborate with data scientists, data engineers, and business stakeholders to understand business needs, and translate that scope into data requirements</li> <li>Identify key business questions and problems to solve for, and generate insights by developing structured solutions to resolve them</li> <li>Lead the development of data products and self-serve tools that enable analytics to scale across the company</li> <li>Build and maintain canonical datasets by developing high-volume, reliable ETL/ELT pipelines using data lake and data warehousing concepts</li> <li>Design metrics and data visualizations with dashboarding tools like Tableau, Sigma, and Mode</li> <li>Be a cross-functional champion at upholding high data integrity standards to increase reusability, readability and standardization</li> </ul> <h2><strong>We're excited about you because you have…</strong></h2> <ul> <li>A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain</li> <li>2-6+ years of experience working in business intelligence, analytics engineering, data engineering, or a similar role</li> <li>Strong proficiency in SQL for data transformation, comfort in at least one functional/OOP language such as Python or Scala</li> <li>Experience in creating compelling reporting and data visualization solutions using dashboarding tools (e.g., Looker, Tableau, Sigma)</li> <li>Familiarity with database fundamentals (e.g. S3, Trino, Hive, Spark), and experience with SQL performance tuning</li> <li>Experience in writing data quality checks to validate data integrity (e.g., Pydeequ, Great Expectations)</li> <li>Strong communication skills and experience working with technical and non-technical teams</li> <li>Comfortable working in fast paced environment, self starter and self organizing</li> <li>Ability to think strategically, analyze and interpret market and consumer information</li> </ul> <p><strong>&nbsp;</strong></p><div class="content-pay-transparency"><div class="pay-input"><div clas