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Ciudad de México, Ciudad de México, México
Onsite
Job Location: Mexico City, Mexico
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.
We are seeking a strategic and execution-focused Data Engineering Director for eCommerce and Consumer data team. In this highly visible global role, you will drive the vision and delivery of best-in-breed data solutions that power our digital experiences and unlock the full value of all our data. Your leadership will enable teams across marketing, product, digital commerce, and customer experience to make smarter, faster, and more personalized decisions at scale. This role will be responsible for delivering data that will help us understand and optimize the digital customer journey, enables hyper-personalization at scale, drives retention and loyalty and fuels advanced AI/ML use cases across the company.
This is a high-impact leadership role at the intersection of data engineering, analytics, and AI/ML enablement—ideal for someone who thrives in building high-performance teams and enterprise-grade data platforms that are the backbone of customer-centric innovation.
About the Job
Lead and grow a high-performing global data engineering team focused on eCommerce and Consumer analytics.
Architect and oversee the implementation of robust pipelines for clickstream data ingestion, transformation, and enrichment from web, mobile, and digital touchpoints.
Partner with analytics, data science, ecommerce engineering and product teams to define reusable, high-quality data products that drive critical KPIs: user engagement, conversion, retention, LTV, churn, etc.
Drive the roadmap for real-time event driven and batch processing architectures, enabling rapid experimentation and decision-making.
Ensure best practices in data governance, quality, lineage, and observability—across large volumes of consumer and behavioral data.
Lead the integration of third-party enrichment sources and identity resolution technologies to build a 360° view of the consumer.
Advance platform capabilities that support AI/ML-driven personalization, segmentation, and journey optimization.
Champion scalable data architecture aligned with our broader modern data platform strategy.
Foster a strong engineering culture that values innovation, quality, speed, and inclusivity.
Champion privacy, ethics, and security in data practices to ensure compliance with regulatory standards and foster consumer trust.
About You
10+ years of experience in data engineering, with at least 3–5 years leading high-performing teams in digital commerce or consumer analytics environments.
Experienced in software development, CI/CD pipelines, testing, operations, on-call rotation setup, and observability
Deep technical expertise in cloud-native data platforms (e.g., GCP, AWS, Azure) and big data frameworks (Spark, Kafka/pub-sub, etc).
Proven experience building and scaling clickstream pipelines and digital data infrastructure, ideally using tools like Segment, Adobe/GA4, etc.
Experience with customer data platforms (CDPs), identity resolution, and privacy-aware data modeling.
Strong command of data warehousing (e.g., BigQuery, Snowflake) and ELT tools (e.g., dbt, Airflow/Kubeflow).
Ability to translate ambiguous business goals into actionable data solutions.
Familiarity with machine learning pipelines and collaboration with data science teams.
Strong cross-functional leadership skills—comfortable aligning with marketing, digital product, engineering, and privacy/legal stakeholders.
Why Join Us
You’ll be part of a company investing deeply in data and AI to transform how we serve and understand our customers. You’ll help shape a data ecosystem that delivers precision, personalization, and performance at scale—and lead a team that's at the forefront of redefining how consumer and digital data power growth.