About the Team:
The Global Strategy & Planning team supports the Delivery Leadership team to define our strategy globally as well as working collaboratively across all functions and markets to assist with identifying areas to improve alignment and execution.
This role sits at the intersection of analytics and strategy as part of the Competition Analytics vertical. The team specializes in developing and scaling best practices for competitive intelligence on a global scale. As a member of this dynamic team, you will play a key role in ensuring that competitive intelligence is accurate, reliable, and actionable. You will focus on building scalable and automated data workflows while collaborating closely with data science and cross-functional teams to drive data-informed decision-making and support growth across markets.
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What You'll Do
- Data Pipeline Engineering & Reliability: Design, monitor, and maintain scalable, reliable data pipelines to ensure timely availability and integrity of data across systems.
- Automation & Process Optimization: Develop and implement global automated solutions to streamline data workflows, reduce manual intervention, and improve operational efficiency.
- Data Quality & Accuracy: Monitor and validate data pipelines to ensure availability and reliability. Build and maintain data quality checks.
- Collaboration: Partner with analytics, engineering, and business stakeholders to understand data requirements and deliver scalable, automated solutions that support Uber Eats globally.
- Reporting Infrastructure: Support the development and automation of reporting systems that enable stakeholders to access and interact with critical metrics and operational insights.
What You'll Need
Technical Skills:
- Strong SQL expertise for data manipulation, transformation, and performance optimization.
- Solid Python skills, particularly for scripting, automation, and working with data processing libraries (e.g., pandas, PySpark).
- Experience with data pipeline and orchestration tools (e.g., Apache Airflow, dbt, Prefect).
- Familiarity with data visualization tools (e.g., Tableau, Power BI, or similar) for supporting self-service reporting.
Problem-Solving: Ability to investigate data issues, identify root causes, and implement solutions.
Attention to Detail: A meticulous approach to ensuring data accuracy and quality.
Communication: Strong skills in explaining data insights and findings to technical and non-technical stakeholders.
Experience: 2+ years in a data analytics, analytics engineering, or automation-focused data roles.
Preferred Qualifications
- Experience with cloud platforms (e.g., AWS, GCP, Azure), especially cloud data warehousing (e.g., BigQuery, Snowflake, Redshift).
- Familiarity with ETL/ELT frameworks and data modeling best practices (e.g., star/snowflake schema).
- Git/version control for managing codebases and deployment processes.
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.