Delivery Data Solutions (DDS) is a horizontal team responsible to transform data @Delivery to meaningful data to support analytics, metrics, power ML models and support KPIs for the domain teams through real time/batch processing. We lead the optimal data resource utilization and data quality for the organization. We provide visibility and standardization of core business metrics powered through the canonical data sets owned by the team. The team is the centre of excellence for data engineering practices across Uber Delivery org. The team creates efficient tools and processes to help people working on data, designs and maintains a holistic view of delivery data, and manages and optimizes delivery data infrastructure resources.

---- What the Candidate Will Do ----

Design, build and own scalable data products and platforms that power business analytics, ML models and decision-making across the Delivery organization.

Lead the architecture and development of batch and real-time data pipelines that process large-scale datasets while ensuring reliability, scalability and maintainability.

Drive the design and standardization of canonical datasets and business metrics used across multiple teams.

Partner closely with product engineering, data science, ML and product teams to translate business requirements into robust data solutions.

Lead initiatives focused on data quality, data governance, and data reliability, ensuring high standards across critical data assets.

Drive performance optimizations and cost efficiency for large-scale data processing systems while maintaining strict SLA commitments.

Influence and establish data engineering best practices, design patterns and technical standards across teams.

Mentor junior engineers and contribute to technical leadership within the data engineering community.

---- Basic Qualifications ----

Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.

Strong programming experience in one or more general-purpose languages such as Java, Python, Go, or similar.

Experience building and operating large-scale data pipelines and distributed data processing systems.

Strong hands-on experience with modern data technologies such as Spark, Hive, Presto/Trino or similar distributed data frameworks.

Experience designing and working with data warehouses, dimensional data models and large-scale analytical datasets.

Strong understanding of data pipeline reliability, performance optimization, and data quality management.

Experience collaborating across teams to design scalable data solutions for complex business problems.

---- Preferred Qualifications ----

Master's degree in Computer Science or a related technical field, or equivalent practical experience.

Experience designing end-to-end data architectures and large-scale data platforms supporting analytics and ML workloads.

Experience working with real-time data streaming systems (e.g., Kafka, Flink, or similar technologies).

Demonstrated experience driving technical initiatives across teams and influencing data engineering best practices.

Experience mentoring engineers and contributing to technical leadership within engineering teams.

Domain experience in marketplace, logistics, or delivery platforms is a plus.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuelds progress. What moves us, moves the world - let's move it forward, together.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.