Senior Data Engineer

At Levi Strauss & Co, we are at the forefront of revolutionizing the apparel industry and redefining the way denim is made. We are propelling one of the world’s most iconic brands into the future by using innovative technologies such as machine learning-powered denim finishes and advanced algorithms to better meet consumer needs and optimize our supply chain. 

Join our innovative Data & ML Platform Engineering organization and lead the charge in transforming the fashion industry. As a Senior Data Engineer, you will have the opportunity to develop groundbreaking solutions that drive our global business forward while being part of a dynamic, cross-continental data community.  

This position is available to candidates located in Mexico, Brazil, Colombia and USA. We invite applications from individuals this location. 

In this role, you will be a key member of the Sales Distribution and Material Management Data Domain team. You will get an opportunity to work on a cloud native and modern data platform, building data pipelines to building data models and transformations to delivering data products and dashboards to our business stakeholders. You will provide technical expertise and operational support to meet the data needs for our businesses. From migrating existing workloads to building advanced cloud solutions, you will help shape and execute strategies to increase agility, improve security, reduce costs, and meet utilization targets. 

You will collaborate closely with cross-functional teams including Analysts, Data Scientists, SREs, and other engineers, focusing on delivering high quality data products that foster a culture of engineering excellence. We seek someone who brings thoughtful perspective, empathy, creativity, and a positive attitude to solve problems at scale. 

Duties and Responsibilities 

• Architect, design, and implement high-performance data pipelines and ETL processes to support large-scale data products. 

• Design, build, and deliver efficient data models and products that align with business needs. Understand requirements fully and come up with robust data models and products while developing solutions tailored to analytical and consumption requirements. 

• Implement data quality, governance, and best practices to ensure consistency, accuracy, and reliability across data products. Establish monitoring and alerting systems to keep stakeholder trust throughout the data lifecycle. 

• Perform root cause analysis and implement preventative solutions. Monitor processes to ensure data quality and performance, using cost analysis to design efficient solutions and minimize overruns. 

• Work closely with stakeholders to grasp requirements, translate them into detailed technical solutions that align with the timelines, and plan incremental delivery. 

• Lead and mentor a team of junior data engineers, with code reviews, sharing best practices for data engineering and fostering a culture of technical excellence. 

• Familiarity with modern software development practices (Agile, CI/CD) applied to data engineering. 

Qualifications 

• 8+ years of experience in data engineering, with a proven record of accomplishment of building and scaling data-intensive applications. 

• Deep understanding of data warehousing concepts, dimensional modeling, and ETL best practices. 

• Strong proficiency in SQL and at least one coding language like Python or Java. 

• Hands-on experience with open-source big data technologies such as Spark, Flink, and Hive. 

• Experience with one of the major public cloud platforms, preferably GCP.  

• Working knowledge in any data transformation libraries like DBT (Data Build Tool), PySpark, or Snowpark. 

• Experience with data visualization tools (e.g., Tableau, Looker). 

• Working knowledge of GitHub/Git Toolkit and CI/CD best practices. 

• Passion for data and an ardent desire to solve complex problems. 

• Collaborative team player capable of interacting effectively with both technical and non-technical team members.

This position can be based in Mexico City or US Remote