Job Summary
This hybrid night shift role focuses on product information and master data management for global order management and trading operations requiring eight to ten years of experience. The candidate will optimize data quality streamline order processes and align product data with retail order workflows to improve operational efficiency and customer outcomes while supporting complex enterprise systems.
Responsibilities
- Drive end to end product information and master data management initiatives to ensure consistent accurate and reliable data across all order management and trading platforms supporting seamless business operations
- Manage data governance activities for product attributes customer records and transactional order data to maintain high data quality standards and reduce downstream processing errors
- Coordinate with cross functional teams such as operations technology and compliance to align product and master data structures with evolving order management and trading requirements
- Monitor and optimize data integration workflows between core order management systems and trading solutions to minimize latency improve data accuracy and support timely decision making
- Analyze complex order flows and product data relationships to identify process gaps and recommend enhancements that lead to more efficient retail order handling and reduced rework
- Implement data validation rules and operational checks within master data and order management processes to prevent data inconsistencies and enhance reliability of reporting and analytics
- Oversee documentation of data models business rules and process maps for product information and master data management to support knowledge sharing and future system enhancements
- Collaborate with teams working in night shift schedules to resolve critical data issues in real time thereby maintaining uninterrupted trading and order processing services
- Guide configuration and maintenance activities in order management modules to ensure product hierarchies pricing structures and fulfillment parameters reflect current business strategies
- Evaluate impacts of new trading features or regulatory changes on product and master data structures and plan remediation steps that maintain compliance and operational stability
- Support continuous improvement by tracking key performance indicators related to data accuracy order cycle time and error rates and by recommending targeted corrective actions
- Coordinate hybrid work model activities to maintain effective communication documentation and handovers across onsite and remote team members ensuring smooth night shift operations
- Contribute to company goals by enabling accurate data driven decision making and by improving customer experiences through reliable order processing and transparent product information
Qualifications
- Possess eight to ten years of hands on experience in enterprise order management and trading systems with a strong focus on product information and master data management practices
- Demonstrate advanced proficiency in configuring and supporting order management solutions including transaction flows fulfillment rules and exception handling tailored to complex business needs
- Bring practical exposure to retail order management scenarios covering pricing promotions catalog management and omnichannel order fulfillment supported by robust product data structures
- Apply deep understanding of master data principles including data modeling data stewardship and data lifecycle management in environments with high transactional volumes
- Utilize strong analytical and problem solving skills to investigate data discrepancies in order and trading systems and to design sustainable corrective and preventive actions
- Show capability to work effectively in hybrid and night shift settings managing stakeholder expectations and maintaining clear written communication across time zones
- Exhibit familiarity with industry best practices for data governance metadata management and data quality monitoring relevant to order management trading and retail domains
À savoir avant de postuler
- Autorisation de travail: Cognizant ne prendra en considération que les candidats à ce poste qui sont légalement autorisés à travailler au Canada sans avoir besoin d'un parrainage de l'employeur, aujourd'hui ou à l'avenir.
- Mesures d’adaptation: Si vous avez un handicap qui nécessite des mesures d’adaptation raisonnable pour effectuer une recherche d’emploi ou poser une candidature, veuillez envoyer un courriel à [email protected] avec votre demande et vos coordonnées.
- L’IA dans notre processus de recrutement: Nous utilisons des outils d'intelligence artificielle (IA) pour trier et évaluer les candidatures efficacement. Notre équipe examine ensuite les candidatures et décide qui passe à l’étape suivante.
- Poste à pourvoir: Sauf indication contraire, ce poste est actuellement vacant et nous cherchons à le pourvoir.
- Exigences linguistiques: Nous demandons à tous les candidats de posséder une connaissance de base de l’anglais afin de faciliter les communications internes. Pour les postes au Québec, la capacité à communiquer efficacement en anglais est requise car vous fournirez des services à et collaborerez avec des parties prenantes anglophones situées hors de la province.
- Inclusion: Cognizant est un employeur souscrivant au principe de l’égalité d’accès à l’emploi. Votre candidature et votre dossier ne seront pas examinés en fonction de la race, de la couleur, du sexe, de la religion, des croyances, de l'orientation sexuelle, de l'identité de genre, de l'origine nationale, du handicap, des renseignements génétiques, de la grossesse, du statut d'ancien combattant ou de toute autre caractéristique protégée par les lois fédérales, provinciales ou locales.
À propos de Cognizant
Cognizant (NASDAQ: CTSH) est un AI Builder et une entreprise de services numériques (ESN) élaborant des solutions complètes d’IA maximisant les investissements pour des résultats concrets. Sa profonde expertise des métiers, des processus et des technologies lui permet d’intégrer dans les systèmes technologiques le contexte unique de chaque organisation de l’ingénierie à la production à l’échelle. Son objectif: améliorer l’efficacité des équipes, créer de la valeur et permettre aux grandes entreprises de rester performantes dans un monde qui évolue rapidement. Pour en savoir plus: cognizant.ai ou @cognizant.
