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Data Architect

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SeniorZdalnie·WarszawaFull-time·Umowa o pracę

#466851·Dodano 19 dni temu·0

Źródło: justjoin.it

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Tech Stack / Keywords

DataArchitectureERDUML ETL

Podsumowanie oferty

Shape and evolve an enterprise data platform for reliable data integration, advanced analytics, and data-driven business decisions. Design its architecture and guide delivery teams, working with Azure Databricks and other Azure data platform technologies.

Wymagania

Proven experience designing and developing scalable enterprise data platforms based on Lakehouse architecture.
Strong knowledge of Azure Databricks and modern cloud-based data processing environments.
Experience creating conceptual, logical, and physical data models.
Practical knowledge of data integration, including ETL/ELT, batch processing, streaming, and data exchange between operational and analytical systems.
Experience defining architectural standards, reusable patterns, and best practices for data modelling, integration, security, and data access.
Strong understanding of data architecture principles and the relationship between data platforms, reporting, and analytics.
Advanced knowledge of data modelling techniques, including ERD and UML.
Experience using Enterprise Architect or comparable tools to document data models, architectures, and data flows.
Ability to manage and maintain an architecture repository containing data models, standards, architectural decisions, integration patterns, and reference documentation.
Familiarity with the Microsoft Azure cloud ecosystem and services supporting enterprise-scale data platforms.
Familiarity with Azure Data Lake Storage, Delta, Microsoft Fabric, Apache Airflow, Unity Catalog, Databricks Asset Bundles, Delta Sharing, Terraform, Infrastructure as Code, and Azure DevOps.

Nice to have:

Familiarity with data management and enterprise architecture frameworks such as DAMA-DMBOK and TOGAF.

Obowiązki

Design and evolve end-to-end data architecture, including data models, ingestion patterns, transformation layers, data products, and consumption interfaces.
Define architectural principles and technical standards for data storage, processing, integration, access, and sharing.
Design scalable data integration solutions for batch and streaming workloads, ETL/ELT processes, and connections between source systems and analytical environments.
Establish best practices for data modelling, metadata management, data lineage, reference data, and business terminology.
Maintain architectural documentation, including data models, integration patterns, design decisions, standards, and reference materials.
Translate business and technical requirements into architectural designs, data structures, and implementation recommendations.
Conduct architecture reviews, document key decisions, and guide delivery teams in applying agreed standards and security principles.
Work with Data Engineers, Analysts, Data Owners, Project Managers, and business stakeholders to ensure solutions meet organizational requirements.
Present architectural recommendations and platform development options to technical and business audiences.

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