About the Role
You’ll collaborate with engineers, analysts, and product stakeholders to understand requirements and shape data architecture that supports business goals. This is a high-impact role that demands strong communication skills, technical depth, and a proactive mindset.
- - - - What the Candidate Will Do ----
- Bring industry experience in data engineering or a related field.
- Partner with cross-functional Safety and Insurance teams across global tech hubs to deliver on Uber’s strategic objectives.
- Design and develop scalable data pipelines for real-time and batch processing to extract, clean, enrich, and load data.
- Enhance data quality through monitoring, validation, and alerting mechanisms.
- Continuously evolve our data architecture to support new products, features, and safety initiatives.
- Contribute to building feature pipelines that support data science models for predictions and business decisions.
- Own end-to-end data solutions—from requirements gathering through to production deployment.
- - - - Basic Qualifications ----
- Bachelor’s degree in Computer Science, Engineering, or a related technical field—or equivalent practical experience.
- 3+ years of professional software development experience, with a strong focus in Data Engineering and Data Architecture .
- Proven ability to work closely with product managers and business stakeholders to gather requirements and design scalable data infrastructure that supports cross-functional needs.
- Advanced SQL expertise , including proficiency with:
- Window functions
- Common Table Expressions (CTEs)
- Dynamic SQL variables
- Hierarchical queries
- Materialized views
- Hands-on experience with big data and distributed computing technologies , such as:
- HDFS
- Apache Spark
- Apache Flink
- Hive
- Presto
- Strong programming skills in Python , with solid understanding of object-oriented programming principles.
- Experience designing and maintaining large-scale distributed storage and database systems , including both SQL and NoSQL solutions (e.g., Hive, MySQL, Cassandra).
- Deep understanding of data warehousing architecture and data modeling best practices.
- Familiarity with major cloud platforms such as Google Cloud Platform (GCP) , AWS , or Azure .
- Working knowledge of reporting and business intelligence tools , such as Tableau or similar platforms.
- - - - Preferred Qualifications ----
- Advanced experience with SQL , including Spark SQL , Hive , and Presto , with a deep understanding of query optimization and performance tuning.
- Hands-on experience with streaming data technologies , such as Apache Kafka , Apache Flink , or Spark Structured Streaming , for building real-time data pipelines.
- Experience working with Apache Pinot or similar OLAP data stores for high-performance, real-time analytics.
- Familiarity with Python libraries for big data processing (e.g., PySpark ) and working knowledge of Scala in distributed data environments.
- Practical experience in deploying and managing data solutions on cloud platforms such as GCP , AWS , or Azure .
For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year.