Analytics Engineer, GTM Data Infrastructure

Analytics Engineer, GTM Data Infrastructure

Door Dash – GTM Data Infrastructure Team

The Go To Market Technology (GTMT) organization enables the growth and productivity of Door Dash Go‑To‑Market teams with reliable data, intelligent workflows, and frictionless experiences. We build systems that streamline business processes to be nimble and effective while serving our Merchants and Customers. We’re looking for analysts to join our GTMT team to build elegant solutions that power Door Dash’s rapid growth.

We’re looking for a business‑savvy data specialist who can think like an engineer and act like an analyst. You will automate high‑impact GTM workflows, rapidly prototype new business processes, and own end‑to‑end data quality across critical systems. You will report to the Manager of the GTM – Data team in our GTM product and engineering organization.

• Partner with Product, Engineering, Data Science & Analytics, Operations, Finance, and other cross‑functional stakeholders to understand needs and deliver data solutions.
• Develop frameworks and scalable processes to streamline reporting, drive decision‑making, and build first‑class scalable data platforms and tools.
• Implement automation solutions, data products, and explore/integrate AI capabilities into data tools and applications to enhance productivity and decision‑making.
• Serve as a strategic partner for the business: identify opportunities and create solutions to automate and scale ad‑hoc requests.
• Build and maintain robust data pipelines and data models using SQL, Python, Airflow, ensuring high data integrity and performance.

• Drive strategic impact through innovative technological solutions.
• Own problem solving and collaborate directly with key business partners.
• Thrive in a dynamic environment and expand your skill set.
• Build diverse expertise across technical and business domains, including AI.
• Tackle ambiguity and solve large, complex problems iteratively.
• Shape data infrastructure to make insights accessible for critical business processes.
• Influence decision making by defining metrics and presenting findings.
• Build scalable solutions and streamline reporting.
• Collaborate cross‑functionally with Product, Engineering, Data Science & Analytics, Operations, Finance.
• Innovate with technology by implementing automation and AI capabilities.

• 4+ years’ experience in analytics engineering in a high‑growth environment.
• Ability to translate unstructured business problems into clear requirements.
• Experience building automation solutions, ETL pipelines, and production‑facing data products.
• Proficiency in SQL and Python, quantitative analysis, and data exploration.
• Strong problem‑solving and analytical skills across detailed and high‑level problems.
• Excellent communication skills and ability to present findings to various audiences.
• Strong interpersonal skills and ability to build relationships across functions.
• Attention to detail, structured thinking, and experience developing error‑reducing processes.
• Master’s degree in Mathematics, Statistics, Economics, Engineering, or related technical field.
• Understanding of engineering standards, code reviews, and testing best practices.

• Knowledge of CI/CD practices and infrastructure as code.
• Deploying, monitoring, and maintaining applications/services in AWS and Dev Ops skills.
• Experience building dashboards in Sigma/Tableau.

• Leadership is part of everyone’s culture.
• We are doers, building solutions that lead the company and industry.
• Continuous learning on the job.
• Customer obsession with mission to grow and empower local economies.
• People make our inspiring goals attainable and drive us to greater heights.

Year‑to‑year starting pay range: $100,600—$148,000 USD, depending on location and experience. Base salary is localized. Includes equity grant opportunities and comprehensive benefits.

401(k) plan with employer matching, 16 weeks paid parental leave, wellness benefits, commuter benefits match, paid time off & sick leave (specifications…