Sr Data Engineer
About The Role 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.
- — What You Will Do —-
- 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.
Basic Qualifications —- Basic Qualifications —-
- 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).
Preferred Qualifications
- 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.
For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year – USD$220,000 per year. You will be eligible to participate in Uber’s bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.