• You will architect and evolve the datalake that is the company's data nervous system — the foundation that feeds, in real time, the dynamic pricing engine, ML models, and the group's business intelligence. • This is an ownership role: you define the multi-tenant Lakehouse architecture, from streaming to the semantic layer, and are responsible for its reliability, governance, and cost. • Design and evolve the data lake on Apache Iceberg over S3 — well-defined layers, partitioning and compaction, time-travel and support for DELETE/UPDATE for LGPD (Brazilian data protection law). • Build real-time ingestion (Kafka, Flink, CDC with Debezium) with controlled schema evolution (Schema Registry) and delivery guarantees. • Model the transformation layer in dbt and orchestrate batch and quality flows in Airflow, from crawler to backfill. • Maintain metric definitions in Cube.js — the single source that feeds BI and AI agents and ensures consistency across the company. • Operate federated and low-latency OLAP queries over the lake, with cost and access isolation by tenant and performant queries. • Ensure data testing, lineage and cost efficiency, keeping the platform reliable as it scales.

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.