Senior Data Software Engineer

Há 2 dias


São Paulo, Brasil Uber Tempo inteiro

Join to apply for the Senior Data Software Engineer role at Uber 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 The Candidate 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 Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field—or equivalent practical experience. 7+ 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. Hands‑on experience with big data ecosystems. Strong Python programming skills and solid understanding of object‑oriented design principles. Experience with large‑scale distributed storage and databases. Deep understanding of data warehousing and dimensional modeling. 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 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. #J-18808-Ljbffr



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