Data Engineer
Levi Strauss & Co.
- locations
- Office, Mexico, D.F., Mexico
- Remote - Mexico
- LEVIS Corporate Office - Remote (CO01), COL
- time type
- Full time
- posted on
- Posted Yesterday
- job requisition id
- R-0139819
JOB DESCRIPTION
Calling all originals: At Levi Strauss & Co., you can be yourself — and be part of something bigger. We're a company of people who like to forge our own path and leave the world better than we found it. Who believe that what makes us different makes us stronger. So add your voice. Make an impact. Find your fit — and your future.
At Levi Strauss & Co., we are revolutionizing the apparel business and redefining the way denim is made. We are taking one of the world's most iconic brands into the next century: from creating machine learning-powered denim finishes to using blockchain for our factory workers' wellbeing, to building algorithms to better meet the needs of our consumers and optimize our supply chain.
Be a part of that transformation by joining our Digital Technology organization, where you will have the chance to build data-driven solutions that impact our Americas business, while connecting with a global data and analytics community.
The Data, Analytics & AI/ML Engineering team at Levi is on a mission to deliver a modern, scalable data platform that turns data into meaningful insights. As a Data Engineer on this team, you will work within the Operations Data Domain , focusing on building and maintaining robust data pipelines, preparing clean, usable datasets, and helping deliver data products that power analytics and decision-making across the company.
If you're a curious and motivated engineer who enjoys working with data, solving problems, and collaborating with others to build scalable solutions, we want to hear from you.
About the Job
Design, develop, optimize and maintain scalable and reliable big data solutions, including data pipelines, data warehouses, and data lakes.
Collaborate with cross-functional teams including data product managers, data scientists, analysts, and software engineers to understand business data requirements and deliver efficient solutions.
Participate in optimizing data storage, processing, and retrieval for large datasets.
Establish scalable, efficient, automated processes for data analysis, model development, validation, and implementation.
Implement and maintain data governance and security best practices to ensure data integrity and compliance with regulatory standards.
Write efficient and well-organized software to ship products in an iterative, continual-release environment.
Reporting key insight trends, using statistical rigor to simplify and inform the larger team of noteworthy story lines that impact the business.
Troubleshoot and resolve performance issues, bottlenecks, and data quality issues in the big data infrastructure.
Guide and mentor junior engineers, fostering a culture of continuous learning and technical excellence.
Communicate clearly and effectively to technical and non-technical audiences.
Contribute internal best practices, frameworks, and reusable components to enhance the efficiency of the data engineering team.
Embody the values and passions that characterize Levi Strauss & Co., with empathy to engage with colleagues from multiple backgrounds.
About You
University or advanced degree in engineering, computer science, mathematics, or a related field
3 to 6 years' experience developing and deploying data pipelines (batch and/or streaming) into production
Experience working with a variety of relational SQL and NoSQL databases
Hands-on experience with cloud-native data services, ideally on Google Cloud Platform ( BigQuery , Pub/Sub, Cloud Functions, etc.)
Familiarity with data warehousing tools such as Snowflake, BigQuery , or RedShift
Experience with dbt (Data Build Tool) for data transformation is a plus
Exposure to big data tools and frameworks such as Hadoop, Spark, or Kafka; familiarity with Databricks is a plus
Proficiency with scripting or programming languages such as Python, Java, or Scala
Experience contributing to framework-based solutions for data ingestion and processing, and/or building Data Lake/Lake House components
Working knowledge of workflow orchestration tools like Apache Airflow is a plus
Familiarity with version control systems such as Github /Git Toolkit
Experience collaborating with stakeholders to provide operational support
Understanding of standard software engineering practices, including unit testing, code reviews, and documentation
Experience with CI/CD pipelines using Jenkins or Github Actions is desirable
Exposure to data visualization tools such as Tableau, PowerBI , or Looker is an asset