Data Architect – Governance, Quality

🕒 il y a 24 jours

🇵🇱 Pologne – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🚰 Ingénieur Data

👻 Score fantôme 14%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Software Mind

Site WebLinkedInTous les Emplois

1001 - 5000 employés

Fondée en 1999

🤖 Intelligence artificielle

☁️ SaaS

📡 Télécommunications

💰 Private Equity Round en 2020-12

Artificial Intelligence • SaaS • Telecommunications

Software Mind est une entreprise technologique spécialisée dans le développement logiciel et les services de transformation numérique. En mettant l'accent sur les solutions IA et cloud, l'entreprise propose une large gamme de services, incluant le développement de logiciels sur mesure, le développement d'applications mobiles et le conseil en cloud. Software Mind dessert divers secteurs tels que les services financiers, les télécommunications, la biotechnologie et les médias, fournissant des solutions personnalisées pour accélérer les transformations numériques et la croissance des entreprises à l'échelle mondiale.

Description

• Design semantic, logical, and conceptual data models based on business domains and organizational processes • Define and standardize the corporate data model as part of the Data Governance initiative • Create and maintain logical and technical reference architectures and design patterns for data domains • Co-create the strategy and roadmap for data architecture development • Collaborate with Data Governance, Data Management, Analytics, AI, and Data Engineering teams to integrate models with data catalog and metadata management tools • Support technical teams in implementing models in data layers • Participate in designing data integration, flow, and quality processes, including data lineage, data contracts, and data quality • Identify and certify authoritative data sources within organizational domains • Monitor compliance of data solutions with Data Governance policies, standards, and architectural recommendations • Support resolution of data conflicts and issues • Create architectural documentation, metamodels, and inter-domain relationship diagrams • Consult on and develop practices for modeling, metadata, and information architecture • Collaborate on the vision, priorities, and directions for data architecture development • Partner with sales and industry teams on technical presales, including discovery workshops, solution design, estimations, and technical proposal and RFP content • Present architectures and recommendations to client stakeholders from engineering teams to C-level • Design and run proofs of concept and technical demos • Evaluate new approaches and tools such as data mesh, streaming-first, and AI-native platforms, and share findings internally and externally

🎯 Exigences

• Experience in Data Governance, Data Quality, Master Data, and Metadata Management projects • Experience in conceptual, logical, and physical data modeling, preferably in a large organization or within complex data ecosystems • Deep knowledge of modern Data Platforms, including Snowflake and Databricks • Practical knowledge of ER, UML, IDEF1X, Data Vault, 3NF, and Kimball/Inmon • Ability to work with data catalogs and metadata management tools such as DataHub, Collibra, Alation, and Atlan • Knowledge of SQL and relational data models • Experience with database systems and data architecture in cloud environments: AWS, GCP, and Azure • Ability to translate business needs into data models with engineering and analytics teams • Understanding of data security, availability, and control principles • Good command of English for reading documentation and community discussions • Knowledge of semantic data layer concepts and technologies, including ontologies, RDF, OWL, GraphQL, dbt Semantic Layer, and Semantic Kernel • Knowledge of Python for automation, model validation, and API integrations • Knowledge of event-driven data architecture • Experience creating and maintaining architectural documentation

🏖️ Avantages

• Flexible and remote cooperation options • International projects with leading global clients • Travels related to international projects • Non-corporate atmosphere • Access to language classes • Access to knowledge-sharing initiatives • Access to private healthcare and life insurance • Access to multisport card

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