14 oct
Uber
Santiago
About the Role
Uber is at the forefront of redefining the future of grocery and retail delivery. From a company that began by transporting people, we have evolved into a platform that delivers nearly anything on-demand. As we continue expanding into groceries, retail, and beyond, we are focused on providing a seamless, scalable experience for our customers, earners, and partners.
The Grocery & Retail Data Engineering Team plays a pivotal role in driving this mission. This team is responsible for building and maintaining robust data platforms that support our fast-growing grocery and retail services. As a Data Engineer in this team, you will be designing, developing, and scaling data solutions that will enable advanced analytics,
operational efficiencies, and data-driven decision-making across various business verticals.
- Basic Qualifications -
- BSc in Computer Science, Engineering, Mathematics, or a related field experience in Software Engineering, with at least 3 years of focused experience in:
1. Programming Languages: Full proficiency in Python, SQL, and Java/Scala.
2. Big Data Technologies: Hands-on experience with Spark, Hadoop, Kafka, Flink or other big data processing frameworks.
3. ETL Development: Designing and building ETL pipelines for processing large data sets.
4. Data Systems Design: Experience designing end-to-end data solutions and complex data architectures.
- Preferred Qualifications -
- Strong knowledge of SQL and database optimization techniques for both relational and non-relational databases.
- Understanding of data warehousing solutions and best practices, including partitioning, indexing, and schema design.
- Experience with cloud-based data services (e.g., AWS Redshift, Google BigQuery, Azure Data Lake).
- Experience working with cloud infrastructure (e.g., AWS, Google Cloud Platform, Microsoft Azure) to deploy and manage scalable data solutions.
- Demonstrated ability to translate complex business requirements into efficient and scalable data models, systems, and analytical tools.
- Familiarity with distributed systems and their associated challenges, including consistency, availability, and fault tolerance.
- Ability to work with both batch and real-time data processing frameworks.
- What the candidate Will Do -
- Collaborate with cross-functional stakeholders, including product managers, data scientists, and software engineers, to design and develop data systems that enable Uber's grocery and retail expansion.
- Build and maintain large-scale data systems such as data warehouses, databases,
and big data infrastructures that power various analytics and business applications.
- Develop scalable ETL (Extract, Transform, Load) pipelines to process and manage high volumes of structured and unstructured data.
- Ensure the reliability, availability, and performance of data systems through continuous monitoring and optimization of distributed data processing frameworks (e.g., Spark, Flink, Presto).
- Lead efforts to improve data modeling practices, defining best practices for schema design and data governance to support business intelligence tools and advanced analytics.
- Create and optimize data workflows to support both operational systems and advanced data analysis, ensuring consistency, integrity, and quality across all data products.
- Support the development and implementation of cutting-edge data architecture, ensuring scalability, fault-tolerance, and efficiency.
- Stay ahead of industry trends and emerging technologies in data engineering to maintain Uber's competitive edge in data solutions.
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