Top Tech Jobs & Startup Jobs

Lead and grow a backend engineering team responsible for DoorDash’s Credits and Refunds, resolution workflows, and policy configuration platform. Own platform migration, distributed-systems architecture, reliability, scaling, configuration safeguards, and integration of machine-learning models into high-volume production workflows. Partner with Product, ML, Fraud, Data Science, and Operations teams while mentoring engineers, shaping technical direction, improving operational excellence, and supporting engineering recruiting.

Leads and develops a backend engineering team, overseeing roadmap execution, architecture, technical quality, hiring, and professional growth. Partners with product managers, business leaders, and cross-functional stakeholders to deliver scalable solutions. The role requires distributed systems expertise, system scaling and performance optimization experience, B2B product development, API and data integration experience, and the ability to lead remote teams in a fast-paced environment.

Build and maintain scalable data models, pipelines, aggregation layers, and self-service analytics. The role includes optimizing ETL/ELT processes, ensuring data quality and reporting reliability, defining KPIs, automating reporting, and developing dashboard products with tools such as Tableau and Sigma. The engineer will collaborate with data engineers, data scientists, and business stakeholders to deliver analytical solutions across the organization.

Build and scale data models, pipelines, aggregation layers, and self-service analytics. Responsibilities include designing analytical data structures, optimizing ETL/ELT processes, defining KPIs, ensuring reliable reporting, automating ad-hoc analyses, standardizing reporting patterns, and developing dashboards using tools such as Tableau or Sigma. The role collaborates with data engineers, data scientists, and business stakeholders to deliver scalable, high-quality data solutions.

Leads a data engineering team responsible for enterprise-scale data solutions, architecture, reliability, and developer enablement. The role combines people leadership—including hiring, coaching, performance management, and team growth—with technical strategy for scalable data platforms, batch and real-time processing, data assets, and reusable components. Partners cross-functionally to drive engineering excellence, innovation, and long-term platform strategy.

Designs and builds scalable data models, ETL pipelines, data lake and warehouse architectures, data quality checks, monitoring routines, and data products. Collaborates with business, engineering, product, and third-party stakeholders to define and collect requirements. Maintains reliable data infrastructure, supports reporting and analytics use cases, and helps onboard new engineers.