At a Glance
- Tasks: Join our team to automate workflows and build scalable data solutions.
- Company: DoorDash empowers local economies through innovative technology and logistics.
- Benefits: Enjoy flexible paid time off, wellness benefits, and comprehensive healthcare.
- Why this job: Shape business strategies while developing your skills in a dynamic environment.
- Qualifications: 4+ years in data analytics; proficient in SQL and Python.
- Other info: Collaborate with cross-functional teams and explore AI capabilities.
The predicted salary is between 72000 - 104000 £ per year.
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. We are looking for analysts to join our Go-To-Market Technology (GTMT) team, where you will build elegant solutions that power DoorDash's rapid growth. Specifically, we are seeking proactive and driven individuals who are eager to dive deep into data, build scalable data platforms/tools, and translate insights into actions that drive our business forward.
We are 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. If you have 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 will 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.
- 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, Analytics, Engineering, or a related technical field.
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.
Why You’ll Love Working at DoorDash
- We are leaders: Leadership is not limited to our management team. It’s something everyone at DoorDash embraces and embodies.
- We are doers: We believe the only way to predict the future is to build it. Creating solutions that will lead our company and our industry is what we do -- on every project, every day.
- We are learners: We’re not afraid to dig in and uncover the truth, even if it’s scary or inconvenient. Everyone here is continually learning on the job, no matter if we’ve been in a role for one year or one minute.
- We are customer obsessed: Our mission is to grow and empower local economies. We are committed to our customers, merchants, and dashers and believe in connecting people with possibility.
- We are all DoorDash: The magic of DoorDash is our people, together making our inspiring goals attainable and driving us to greater heights.
Our Commitment to Diversity and Inclusion
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.
Analytics Engineer, GTM Data Infrastructure employer: DoorDash
Contact Detail:
DoorDash Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer, GTM Data Infrastructure
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as SQL, Python, and Airflow. Having hands-on experience or projects showcasing your skills with these tools can set you apart during discussions.
✨Tip Number 2
Network with current or former employees of DoorDash, especially those in the GTM Data team. Engaging in conversations about their experiences can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss how you've previously tackled complex data problems and automated processes. Be ready to share specific examples that demonstrate your problem-solving skills and ability to work cross-functionally.
✨Tip Number 4
Stay updated on industry trends related to data analytics and automation. Being knowledgeable about the latest advancements can help you engage in meaningful conversations during interviews and show your enthusiasm for the role.
We think you need these skills to ace Analytics Engineer, GTM Data Infrastructure
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analytics, particularly in high-growth environments. Emphasise your proficiency in SQL and Python, as well as any experience with automation solutions or building data pipelines.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your skills align with the responsibilities outlined in the job description, such as developing scalable data platforms and collaborating with cross-functional teams.
Showcase Problem-Solving Skills: Provide specific examples in your application that demonstrate your problem-solving abilities. Highlight instances where you've automated processes or improved data integrity, as these are key aspects of the role.
Highlight Communication Skills: Since strong communication skills are essential for this position, include examples of how you've effectively presented findings to stakeholders or collaborated with different teams. This will show that you can influence decision-making and work well in a team environment.
How to prepare for a job interview at DoorDash
✨Understand the Role
Make sure you have a clear understanding of the Analytics Engineer position and its responsibilities. Familiarise yourself with the tools mentioned in the job description, such as SQL and Python, and be prepared to discuss how your experience aligns with the role.
✨Showcase Problem-Solving Skills
Be ready to share specific examples of how you've tackled complex data challenges in the past. Highlight your ability to translate unstructured business problems into actionable insights, as this is crucial for the role.
✨Demonstrate Collaboration
Since the role involves partnering with various teams, prepare to discuss your experience working cross-functionally. Share examples of how you've successfully collaborated with product, engineering, or analytics teams to deliver data solutions.
✨Prepare for Technical Questions
Expect technical questions related to data pipelines, automation, and AI capabilities. Brush up on your knowledge of best practices in data management and be ready to discuss how you've implemented these in previous roles.