Role Description Un des rôles de GS1 est d’accompagner les entreprises de différents secteurs dans la co-conception de modèles de données communs permettant de partager l’information sur les produits et faciliter le développement de leur commerce physique ou digital dans un contexte d’interopérabilité internationale. Votre rôle : En tant que Data Modeler Senior, vous concevrez et ferez évoluer les modèles de données autour des enjeux liés à l’échange des informations produits pour le compte de nos clients. Vos missions principales : - Contribuer activement aux phases amont des projets : études de cadrage, analyse des enjeux et cohérence des choix techniques - Recueillir, comprendre et analyser les besoins métiers en collaboration étroite avec les utilisateurs - Concevoir et définir des modèles de données standards répondant aux attentes métiers, et rédiger les spécifications fonctionnelles et techniques associées - Participer à l’élaboration et à l’harmonisation des standards de modèles de données à l’échelle internationale, en portant la vision et les besoins du marché français - Apporter un support expert de niveau 3, en interne comme en externe, et accompagner les équipes dans la résolution des problématiques complexes - Définir et garantir les critères de conformité des services et solutions avec les standards en vigueur - Assurer une veille technologique continue afin d’anticiper les évolutions et promouvoir les meilleures pratiques Les secteurs prioritaires que vous accompagnerez : Produits alimentaires, produits droguerie – parfumerie - hygiène, produits électroniques, textile, santé, construction, industries techniques, … Qualifications - Formation généraliste Bac+5 (Data, Project Management…) - Première expérience minimum de 5 ans dans le domaine de la data analyse, modélisation de data ET de la chefferie de projets. - Connaissance de l’usage de l’IA. - Maitrise des langages XML et XPath, des méthodes de modélisation (UML, …) et les concepts de sémantique, de taxonomie et d’ontologie. - Connaissance des outils de type PIM (Product Information Management) et DAM (Digital Asset Management) Requirements - Empathie et sens du relationnel pour animer des écosystèmes variés - Curiosité intellectuelle et appétence pour l'innovation - Rigueur et méthode dans l'organisation du travail - Orientation résultats et culture de la performance - Autonomie et capacité à prendre des initiatives - Leadership pour fédérer et convaincre Benefits - Un rôle à impact - Participation concrète aux enjeux de l'économie circulaire et durable - Reconnaissance de votre expertise au niveau France, Europe et International - Position centrale dans l'animation d'écosystèmes stratégiques - Contribution à des projets innovants (IA, digitalisation) - Un environnement stimulant - Diversité des secteurs et des problématiques - Organisation à la fois locale et internationale - Culture collaborative et bienveillante - Bureaux au cœur de Paris Processus de candidature - Préqualification téléphonique ou visio avec une Talent Manager. - Entretien physique avec le Responsable Standardisation et la Talent Manager. - Entretien final en présentiel avec le Directeur des Opérations et la Directrice des Ressources Humaines.

Role Description Harbor is looking for detail-oriented and committed Data Quality Professionals (DQPs) to join our growing Managed Services team. As a DQP, you’ll play a key role in helping our clients maintain accurate, high-quality data that supports their business development and relationship management efforts. This is a remote position ideal for individuals who thrive in a structured, flexible work environment with a strong emphasis on quality, accuracy, and independence. Join our team as a Data Quality Professional and make a real impact by delivering accurate, high-quality data that helps our clients succeed. Hourly Pay Rate: $15.00 per hour Responsibilities: - Log in and complete assigned work each week according to deadlines - Review and update client data accurately based on provided Style Guides - Research and validate information using internal and external data sources - Resolve data discrepancies and merge duplicate records - Follow standardized procedures for general data clean-up projects - Exercise sound judgment in determining accurate data - Review audit feedback weekly, correcting any errors and implementing coaching guidance - Communicate issues or blockers proactively with your team - Attend and contribute to team meetings Qualifications - You bring 3+ years of professional work experience or similar, ideally in a detail-driven role - You follow directions carefully and execute tasks with high accuracy - You have strong communication and collaboration skills, especially in virtual settings - You are technically proficient and comfortable using software tools and systems - You are self-motivated, organized, and able to manage your time independently - You take pride in your work and are committed to delivering a high standard of quality - You maintain confidentiality and demonstrate discretion when handling sensitive information Requirements - Reliable, high-speed internet connection - A quiet, dedicated workspace free from distractions during work hours Benefits - Work from home in a fully remote position with a flexible schedule - No dress code – wear what’s comfortable - No commute – save time and money - Supportive team environment with accessible Quality Specialists and Client Managers - Opportunities for advancement – we promote internally and recognize talent

• Lead, mentor, and develop a team of data engineers, setting clear goals, expectations, and growth plans. • Conduct performance reviews, provide ongoing coaching, and support career development across the team. • Manage resourcing, capacity planning, and workload balancing across multiple projects and clients. • Foster a collaborative, inclusive, and high-performing engineering culture. • Own end-to-end delivery of data engineering initiatives, ensuring quality, timeliness, and alignment with business goals. • Plan, prioritize, and track team workstreams across client onboarding, migrations, and platform enhancements. • Remove blockers, manage risks and dependencies, and escalate issues appropriately to leadership. • Partner with project and program managers to set realistic timelines and commitments. • Provide technical direction for ETL/ELT development using Azure Data Factory, dbt, Snowflake, Salesforce, and related platforms. • Review and guide data architecture, models, warehouses, data lakes, and data vault designs for scalability and maintainability. • Ensure adoption of engineering best practices for integration, transformation, testing, and deployment. • Make build-versus-buy and tooling recommendations in partnership with the Director. • Ensure robust data quality frameworks, validation, and monitoring are implemented across pipelines. • Uphold data accuracy, integrity, security, and compliance, including PHI/PII considerations. • Establish standards and documentation for data flows, architecture, and transformations. • Drive resolution of performance, reliability, and cost-efficiency issues across the platform. • Partner with BI, analytics, product, and business teams to align data solutions with reporting and consumption needs. • Communicate progress, risks, and technical concepts clearly to both technical and non-technical stakeholders. • Contribute to roadmap planning and prioritization of data initiatives across the organization. • Identify and implement improvements to engineering processes, automation, and operational efficiency. • Evaluate emerging tools, technologies, and frameworks to advance team capability. • Stay current with industry trends in data engineering, cloud platforms, and big data technologies. • Perform other related duties as assigned by leadership. • Directly manages a team of data engineers, including hiring, performance management, and professional development. • Provides technical and career mentorship and leads cross-functional engineering workstreams.

• Build and own Sardine’s internal data infrastructure, integrating CRM, marketing, product, finance, and operational systems into a cohesive, well-modeled data warehouse. • Own the data warehouse partitioning strategy, access controls, and security architecture in close partnership with the Security and Infrastructure teams to meet compliance and performance requirements. • Take full ownership of billing data infrastructure, including backend warehouse tables, data models, and ongoing maintenance. • Design, implement, and own ETL/ELT pipelines to pull and merge data from multiple internal and external systems, ensuring clean, reliable, and scalable data flows across the organization. • Partner with data science, engineering, revenue operations, and executive stakeholders to define and track KPIs, ensuring business decisions are grounded in data. • Serve as the connective tissue between Revenue Operations, Business Operations, and Product/Eng, translating complex requirements into elegant data solutions. • Champion data quality and governance, ensuring insights are consistent, trustworthy, and well-documented. • Build dashboards and analytics that provide key insights for executive leadership, GTM, product, and finance teams. • Analyze data to identify the best ways to deliver value to clients and inform product decisions.