Job description

Established in 1981, GUESS began as a jeans company and has since successfully grown into a global lifestyle brand. Guess?, Inc. designs, markets, distributes and licenses a lifestyle collection of contemporary apparel, denim, handbags, watches, eyewear, footwear and other related consumer products.

Guess? products are distributed through branded Guess? stores as well as better department and specialty stores around the world.

As of January 30, 2021, the Company directly operated 1,046 retail stores in the Americas, Europe and Asia.

The Company’s partners and distributors operated 524 additional retail stores worldwide.

As of January 30, 2021, the Company and its partners and distributors operated in approximately 100 countries worldwide. For more information about the Company, please visit



Reporting directly to the MIS Data Office Director, the Data Warehouse Engineer will be in contact with each department to find out their needs and adapt statistics accordingly.

You will get a chance to be responsible for the maintenance and the improvement of all the data flows in the data and analytics platforms, work within a diverse team with dynamic strengths that shares your real passion for premium fashion. You will have the chance to be part of a truly iconic global brand, with the opportunity to learn and progress in your career.


  • Conduct and participate in requirement and data analysis
  • Design, prototype, implement and maintain innovative solution on analytic platforms to meet user requirements and reusability of all required data for reporting
  • Integrate and transform new data sources (internal and external) by creating a full pipeline from ingestion to ETL process
  • Optimize and expand the Data & Analytics platform data flows and data models, supporting the Data Scientists or Business Intelligence Manager in deploying analytics products
  • Define and document detailed Data Engineering processes to guarantee efficient building and support of the data & analytics platform
  • Ensure and monitor high data quality standards with focus on data consistency
  • Developing corrective actions, solutions, and improvements of existing database applications


  • 5-10 years of experience in the DWH field
  • Experience in Technical Analysis and Data analytics
  • Understanding of database theories, structures, categories, properties, and best practices
  • Strong Experience in the SQL Language
  • Excellent knowledge and proven professional experience with ETL tools
  • Experience with Data Modelling and ERWIN tool
  • Work with structured and unstructured Data
  • Experience in data cure, cleansing, validation, harmonization and transformation
  • Proficient in best practices for writing code that is maintainable and secure
  • Excellent attention to detail and good analytical and problem-solving experience
  • Ability to independently identify and interpret stakeholders needs and requirements
  • Self-motivated and proactive with ability to work in fast paced environment and under pressure
  • Ability to manage own time to tight deadlines as well as commit and prioritize work duties and tasks
  • Ability to work in virtual teams and matrixed organizations
  • Proven understanding of fashion processes
  • Ability to write data mapping, data dictionary, data transformation documents, understand system architecture, Ability to document the data flows
  • Project Governance & Management SCRUM, Agile
  • Excellent presentation and report writing skills
  • Strong analytical and problem-solving capabilities
  • Excellent English (written/verbal), additional language(s) are an advantage
  • Excellent communication skills and a demonstrable ability to communicate with (internal) customers as well as management at all levels
  • Knowledge of Oracle and Snowflake as well as ETL solutions such as ODI and Matillion is a plus
  • Knowledge of Microstrategy and/or Power BI is a plus
  • Knowledge of programming languages like Python, R, Java is a plus
  • Experience in API and microservices architecture is a plus

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