Engineering Manager, Supply Mobilization Experience

As an Engineering Manager for Supply Mobilization Experience at DoorDash, your responsibilities include leading a team of engineers, setting the technical vision, and developing intelligent mobilization systems. You'll work collaboratively with cross-functional teams to optimize delivery efficiency, drive engagement through personalized incentives, and leverage machine learning for predictive mobilization.

To qualify for the Engineering Manager position at DoorDash, candidates should have a BS, MS, or PhD in Computer Science or a related field, along with at least 2 years of engineering leadership experience managing backend, mobile, and machine learning engineers. Additionally, having 7+ years of industry experience and demonstrating a strong technical leadership ability are essential.

Essential skills for the Engineering Manager role at DoorDash include strong leadership abilities, hands-on technical proficiency, and a solid product sense. Candidates should be impact-driven, capable of navigating complex business challenges, and open to feedback, showcasing the humility necessary for a collaborative work environment.

DoorDash supports the professional growth of Engineering Managers by fostering a culture of technical excellence and innovation. The company encourages mentorship and collaboration across teams, providing opportunities for engineers to tackle high-scale challenges and develop their leadership skills further.

As an Engineering Manager at DoorDash overseeing the Supply Mobilization Experience, your impact on Dasher experience will be significant. By developing systems that optimize Dasher mobilization, you help ensure they are positioned effectively to meet demand, ultimately leading to increased earnings and reduced downtime.

In an Engineering Manager role, it's vital to prioritize projects based on their business impact and alignment with strategic goals. I assess factors like project urgency, team capabilities, and resource availability to create a strategic roadmap, ensuring transparent communication with my team throughout the process.

My leadership style emphasizes collaboration and empowerment. I believe in fostering a culture where team members feel appreciated, encouraged to share their ideas, and involved in decision-making processes. This approach not only increases morale but also drives innovation and ownership within the team.

When conflicts arise, I promote open communication, facilitating discussions between involved parties to ensure each perspective is heard. I believe in seeking common ground and focusing on shared goals, helping resolve disputes amicably while maintaining a positive working environment.

I focus on both qualitative and quantitative metrics such as efficiency improvements, engagement levels, and overall team productivity. Additionally, analyzing feedback from Dashers helps in understanding the impact of our initiatives on user experience, guiding future decisions.

I encourage team members to engage in continuous learning by providing access to relevant training resources, workshops, and conferences. Promoting knowledge exchange within the team also allows us to share cutting-edge techniques and tools that keep our skills sharp.

I’ve encountered various challenges, including unexpected technical issues and shifting project requirements. I prioritize agile methodologies to adapt quickly and effectively, ensuring my team can pivot and refocus as needed, always maintaining product quality and delivery timelines.

I approach mentoring by providing guidance while allowing new engineers to take initiative. I encourage them to tackle real challenges while also providing regular feedback and support, creating an open environment where they can learn and develop confidence in their abilities.

I have extensive experience incorporating machine learning into engineering projects, particularly in optimizing delivery systems. I ensure that the team is adequately trained in machine learning principles and facilitate collaboration with data scientists to maximize the solutions we build.

Balancing technical debt with new feature development is crucial. I advocate for allocating specific sprint cycles for addressing technical debt, while also ensuring that the team maintains a strategic focus on delivering new features that add significant value to the product.

I measure team productivity through various metrics, such as the velocity of work completion, quality of output (fewer bugs and issues), and team engagement scores. Regular one-on-one check-ins also provide insight into individual contributions and areas needing support or improvement.