Analytics Engineer, GTM Data Infrastructure

Salary

$100,600—$148,000 USD

Location

San Francisco, CA; Tempe, AZ; Seattle, WA; New York, NY

About the Team

The Go To Market Technology (GTMT) organization enables the growth and productivity for DoorDash Go-To-Market teams with reliable data, intelligent workflows, and frictionless experiences that move at the speed of DoorDash. We build systems that streamline business processes to be nimble and effective while serving the needs of our Merchants and Customers.

About the Role

We're looking for a business-savvy data specialist who can think like an engineer and act like an analyst. You'll automate high-impact GTM workflows, rapidly prototype new business processes, and own end-to-end data quality across critical systems. If you've built internal tools, scripted away manual reporting pain, or unified Salesforce data across platforms — we want to talk to you.

You will be reporting to the Manager of the GTM - Data team in our GTM product and engineering organization.

Responsibilities

Partner with Product, Engineering, Data Science & Analytics, Operations, Finance, and other cross-functional stakeholders to understand their needs and deliver data solutions to meet business objectives.
Develop frameworks and scalable processes to streamline reporting, drive decision-making, and build first class scalable data platforms/ tools to deliver data quickly, reliably, and accurately.
Implement automation solutions and explore/integrate AI capabilities into data tools and applications to enhance productivity and decision-making.
Be 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 tools like SQL, Python, Airflow, ensuring high data integrity and performance.

You’re excited about this opportunity because you will:

Drive Strategic Impact: Play a pivotal role in shaping business objectives through the implementation of innovative technological solutions.
Own Problem Solving: Enjoy the autonomy to directly address and resolve challenges in collaboration with key business partners.
Embrace Continuous Evolution: Thrive in a dynamic environment where you'll encounter new challenges and opportunities to expand your skillset.
Develop Diverse Expertise: Continuously enhance both your business acumen and technical capabilities across a wide range of problem domains — including exploring and applying AI capabilities to automate workflows, improve decision-making, and drive innovation in GTM operations
Tackle Ambiguity: Embrace the challenge of solving large, complex problems using an iterative and data-driven approach.
Shape Data Infrastructure: Be at the forefront of transforming and managing data to make it insightful and accessible for critical business processes.
Influence Decision Making: Define and monitor key metrics, build insightful dashboards, and present findings to senior leadership, directly influencing strategic decisions.
Build Scalable Solutions: Develop robust data pipelines and scalable processes that streamline reporting and drive prioritization.
Partner Cross-Functionally: Collaborate closely with Product, Engineering, Data Science & Analytics, Operations, Finance, and other teams to deliver data solutions and meet business objectives.
Innovate with Technology: Explore and implement automation solutions and AI capabilities to enhance data tools and applications.

We're excited about you because you have:

4+ years of experience in data analytics in a high-growth environment.
Ability to translate unstructured business problems into clearly defined requirements with minimal oversight.
Ability to build automation solutions to improve revenue efficiency and scale business processes.
Proficient in SQL and Python and quantitative analysis; you can deep dive into large amounts of data, draw meaningful insights, dissect business issues, and draw actionable conclusions.
Strong problem-solving and analytical skills with the ability to transition between detailed data and high-level business problems.
Great communication (listening, written, and oral) skills with the ability to present findings & recommendations targeted to the audience in question.
Strong interpersonal skills, with the ability to build relationships and trust across functions and work collaboratively.
Strong attention to detail, structured thinking, and experience developing processes to reduce human error.
Master’s degree in Mathematics, Statistics, Economics, Engineering, or a related technical field.
Good understanding of development processes and best practices like engineering standards, code reviews, and testing.

Nice to Have:

Knowledge of CI/CD practices and infrastructure as code.
Deploying, monitoring, and maintaining applications/services in AWS.
Experience building dashboards for performance analysis.

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