Job
Description
we're looking for a seasoned Data Architect to lead the design and build of a scalable, future-ready data foundation for Uber s Scaled Solution platform. This role will own the end-to-end data solution design - defining the data model and guiding engineers and analysts to implement it as specified. It s a mission-critical role that will shape how we manage both structured and unstructured data, model complex user journeys, and enable data-driven insights to track and accelerate the success and growth of Scaled Solution. What you'll Do: Architect the end-to-end data platform for Scaled solutions tech, including pipelines, storage, and instrumentation Define scalable data models across complex domains: onboarding, assessments, gig management, tasks, demand, and user events Ensure proper version control, lineage, and governance for key datasets (eg, hierarchical gig data, user tasks, assessment flows) Guide engineering teams on accurate data instrumentation, especially in complex scenarios (eg, email changes during onboarding) Partner with cross-functional stakeholders to translate business needs into robust data architecture Design AI-ready data foundations to support automation, predictive analytics, and text/voice-based agentic interfaces Monitor and evolve architecture to support ongoing feature launches and increasing data volume What you'll Need: 10+ years of overall experience in data and analytics domain 8+ years of experience in data architecture, solution architecture, or data modeling Proven expertise designing and building successful data architecture with high-volume, structured and unstructured datasets on Hadoop and Hive based big data platforms Hands on experience of logical and physical data modeling for user journeys, event tracking, and multi-entity relationships on Hive metastore Deep understanding of Hive, Hudi, Airflow, Pinot, and Flink, with practical experience using them to design and implement modern, scalable data solutions Strong expertise in advanced SQL for complex data transformations, modeling, and performance optimization Proven ability to lead cross-functional teams, guiding data engineers and analysts to design, build, and maintain data pipelines and models aligned with architectural standards Bonus points, if: Experience with modern data stacks and tools (eg, Snowflake, dbt, Airflow, BigQuery, Kafka) Experience designing for AI/ML applications or agentic systems is a strong plus Clear understanding of how to design data platforms and architectures optimized for agent analytics, including data modeling, real-time data flow, context awareness, and integration with LLMs or Agentic AI systems Exposure to tools like Looker, Tableau, or Excel is a plus Experience working in a matrixed organization, aligning with Product and Engineering teams on reporting data instrumentation and schema design Strong leadership, communication, and interpersonal skills to effectively collaborate, influence, and drive alignment across teams
