Data Engineer - Analytics and Supply Chain Data

About ALDO Group

The ALDO Group is an international enterprise that has been creating and marketing shoes and fashion accessories for over 50 years. With nearly 1,500 stores in over 100 countries, the organization stands out thanks to its two signature brands, ALDO and Boutique Spring, as well as being the primary partner of Sperry in North America. The company is also a recognized wholesaler and supplier within the industry, specializing in the design, supply, and distribution of shoes, handbags, and accessories. Its diverse portfolio includes major brands such as ROXY, Brooks Brothers, Ted Baker, Hunter, and G.H.BASS. The ALDO Group is headquartered in Montreal and also has international offices in Europe and Asia. For more information, visit www.aldogroup.com.

Enjoy recognition of value, flexible work options, on-site complementary benefits, generous discounts, and the pride of being part of a brand that places people, the planet, and its partners at the heart of everything.

The ALDO Group is seeking a Data Engineer to join the supply chain organization, integrated within the Data and Analytics ecosystem. This role is responsible for designing, developing, and maintaining data solutions to integrate external and cross-functional data sources into the organization's analytical platform, as well as supporting the migration of existing Power BI reports to Amazon QuickSight.

Reporting to the Supply Chain Manager with a functional link to the VP of Data, AI, and Development, this position bridges the needs of the supply chain business with the company's data engineering standards. The Data Engineer will work within the existing AWS technology stack, collaborate closely with the central data engineering team, and ensure that the supply chain data products are reliable, well-governed, and aligned with the organizational architecture.

The ideal candidate has practical experience in building data pipelines in an AWS environment, comfort with diverse external data sources, sometimes unstructured (Excel files, flat files, PDFs, direct integrations, and potentially EDI flows), as well as practical understanding of BI tools. Experience in the supply chain domain and knowledge of data science concepts are appreciated but not mandatory.

Main Responsibilities

• Design, develop, and maintain data ingestion pipelines to integrate external sources (Excel, CSV, PDF, direct integrations, and potentially EDI) into Amazon Athena and the AWS data lake
• Lead the migration of existing Power BI dashboards and reports to Amazon QuickSight, including data layer preparation, semantic modeling, and result validation against source data
• Collaborate with supply chain stakeholders to understand reporting and analytical needs, define data contracts, and deliver reliable datasets supporting operational and strategic decision-making
• Build and maintain scalable data models for supply chain analytics, ensuring consistency between raw, curated, and consumption layers within the company's data architecture
• Work within the AWS technology stack including Athena, AWS Glue, S3, Redshift, dbt, Apache Hudi, and Lambda to develop and deploy robust data flows aligned with company standards
• Implement and maintain data quality controls, validation rules, and observability mechanisms to ensure reliable data for reporting, dashboards, and downstream applications
• Diagnose and resolve incidents related to data processing and quality, including root cause analysis and implementation of durable fixes
• Collaborate with the central data engineering team to align on platform standards, code review practices, and architectural patterns
• Maintain clear documentation of pipelines, data models, and operational procedures to facilitate maintainability and onboarding of new team members
• Stay up-to-date with best practices in data engineering, analytics, BI tools, and data enablement for the supply chain

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, or a related field
• Three years or more of practical experience in data engineering, with a focus on building and operating data pipelines in production
• Experience in designing, developing, and maintaining data solutions using AWS technologies including Athena, AWS Glue, S3, and related services; experience with Redshift, dbt, Apache Hudi, and Lambda is a significant asset
• Strong proficiency in Python and SQL for data transformation, orchestration, and automation
• Practical experience in ingesting and normalizing data from diverse external sources including Excel/CSV files, PDFs, APIs, and file-based integrations
• Practical knowledge of BI platforms, with hands-on experience in Power BI, Amazon QuickSight, or both; experience in migrating between BI tools is a significant asset
• Solid understanding of data modeling, data architecture, and lakehouse patterns for analytical platforms
• Strong communication skills and ability to collaborate effectively with technical teams and non-technical stakeholders
• Experience in contributing to platform standards, documentation, and operational processes is a significant asset
• A Welcoming Work Environment

We strongly believe that the diversity of backgrounds, perspectives, and identities is an essential richness for the ALDO Group. We encourage applications from all walks of life and are committed to providing a safe, respectful, and equitable work environment where every individual can reach their full potential and make their mark.

*Note: The use of masculine in this document is solely to lighten the text and applies without gender discrimination.* #LI-NM1