Sr Data Engineer

Uber • San Francisco, CA

125d • $198,000 - $220,000 • Remote

About The Position

We're looking for a Senior Data Engineer who thrives on solving complex data challenges and architecting scalable, reliable systems. You'll play a critical role in designing, building, and evolving Uber's Safety & Insurance data ecosystem—enabling the next generation of safety, risk, and compliance products. As a senior member of the team, you will lead end-to-end data initiatives—from conceptual design through production deployment—while mentoring other engineers and influencing technical direction across multiple domains. This role demands strong technical depth, a passion for data excellence, and the ability to partner effectively with cross-functional stakeholders across product, analytics, and platform engineering.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field—or equivalent practical experience.
• 5+ years of professional experience in Data Engineering, Data Architecture, or related software engineering roles.
• Proven experience designing and implementing scalable data pipelines (batch and streaming) that support mission-critical applications.
• Advanced SQL expertise, including window functions, common table expressions (CTEs), dynamic SQL, hierarchical queries, query performance optimization and materialized views.
• Hands-on experience with big data ecosystems, such as Apache Spark (PySpark or Scala), Apache Flink, Hive / Presto, Kafka (real-time streaming).
• Strong Python/Go programming skills and solid understanding of object-oriented design principles.
• Experience with large-scale distributed storage and databases (SQL + NoSQL), e.g., Hive, MySQL, Cassandra.
• Deep understanding of data warehousing and dimensional modeling (Star/Snowflake schemas).
• Experience on cloud platforms such as GCP, AWS, or Azure.
• Familiarity with Airflow, dbt, or other orchestration frameworks.
• Exposure to BI and analytics tools (e.g., Tableau, Looker, or Superset).

Nice To Haves

• Expertise in distributed SQL engines (Spark SQL, Presto, Hive) and deep understanding of query optimization.
• Hands-on experience building streaming and near-real-time pipelines using Kafka, Flink, or Spark Structured Streaming.
• Knowledge of OLAP systems such as Apache Pinot or Druid for real-time analytics.
• Experience developing data quality frameworks, monitoring, and automated validation.
• Proficiency in cloud-native data solutions (e.g., BigQuery, Redshift, Snowflake).
• Working knowledge of Scala or Java in distributed computing contexts.
• Demonstrated ability to mentor junior engineers and establish best practices for data infrastructure.

Responsibilities

• Design, build, and maintain scalable data pipelines for batch and streaming data across Safety & Insurance domains.
• Architect data models and storage solutions optimized for analytics, machine learning, and product integration.
• Partner cross-functionally with Safety, Insurance, and Platform teams to deliver high-impact, data-driven initiatives.
• Ensure data quality through validation, observability, and alerting mechanisms.
• Evolve data architecture to support new business capabilities, products, and feature pipelines.
• Enable data science workflows by creating reliable feature stores and model-ready datasets.
• Drive technical excellence, code quality, and performance optimization across the data stack.
• Mentor and guide engineers in data engineering best practices, design patterns, and scalable architecture principles.

Benefits

• Base salary range for this role is USD$198,000 per year - USD$220,000 per year.
• Eligible to participate in Uber's bonus program.
• May be offered an equity award & other types of compensation.
• Eligible for various benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Industry: Transit and Ground Passenger Transportation
• Education Level: Bachelor's degree