Data Engineer - Growth and Marketing Platform

The Growth and Marketing Platform Data Team is looking for a highly skilled and passionate Data Engineer I to build and scale Uber’s data infrastructure. In this role, you’ll develop high-performance data pipelines, real-time streaming systems, and robust data architectures that power Uber’s growth and marketing initiatives.

You’ll collaborate with Product Managers, Data Scientists, Data Platform Engineers, and Marketing Operations to design scalable, efficient, and reliable data solutions that drive business impact. This role requires technical excellence, problem-solving skills, and a team-first mindset to thrive in Uber’s fast-paced environment.

What You’ll Do

• Design, develop, and maintain scalable data pipelines and backend services for processing large-scale web event analytics.
• Lead the development of core data infrastructure, ensuring high availability, performance, and reliability.
• Solve complex challenges at the intersection of low latency, high correctness, and full determinism.
• Architect and optimize data models, ETL/ELT workflows, and distributed data processing frameworks.
• Participate in code reviews, mentor junior engineers, and enforce best practices in data engineering.
• Diagnose and resolve data quality issues, ensuring accuracy, efficiency, and security.

What You’ll Need

• No more than 2-3 years of experience in data engineering or backend software development.
• Proficiency in Python, SQL, Java, or Scala for data pipeline development.
• Expertise in Big Data frameworks (e.g., Spark, Flink, Presto, MapReduce) and distributed computing.
• Strong SQL skills with experience in data modeling and query optimization.
• Hands-on experience with ETL pipeline development and data warehousing.
• Knowledge of Hadoop ecosystem technologies (HDFS, Hive, Oozie, Airflow).
• Ability to design and implement scalable data architectures that drive business impact.

Preferred Qualifications

• Experience with real-time data streaming (e.g., Flink, Kafka).
• Background in AdTech or large-scale data analytics.