Solution Architect | Data Platform

Elitmind is a consulting company specializing in Data & AI solutions as a key Microsoft partner in Poland. The company builds enterprise-scale data platforms and AI foundations across various industries and technologies, enabling intelligent organizations through data and analytics. Projects involve Microsoft, Databricks, and Snowflake ecosystems, offering exposure to evolving technologies.

• Strong practical knowledge of Azure and its data platform ecosystem.
• Experience designing and implementing enterprise-scale Data Platforms, Data Warehouses, Data Lakehouses, or Delta Lake solutions.
• Hands-on experience with Databricks, including Delta Live Tables and Unity Catalog.
• Good understanding of Azure infrastructure, networking, and identity components.
• Very good understanding of the Data perspective of the Cloud Adoption Framework and basic understanding of the Enterprise perspective.
• Experience designing architecture that covers connectivity, authentication, authorization, CI/CD, data access, governance, scalability, and cost management.
• Experience working directly with clients and various technical and business stakeholders.
• Very good command of English.

Nice to have:

• Design Thinking
• HANA

• Gather requirements and translate business and technical needs into data platform architectures.
• Design enterprise-scale Data Platforms, Data Warehouses, Data Lakehouses, ETL processes, and Machine Learning solutions.
• Identify where AI can add value within a data platform and help clients translate potential use cases into practical platform requirements.
• Consider how data platforms should evolve to support AI-driven solutions, including data availability, access, governance, and scalability.
• Define architecture covering connectivity, authentication, authorization, CI/CD, data access, governance, scalability, and cost management.
• Work with clients on data strategy and help shape practical approaches for adopting and modernizing cloud data platforms.
• Prepare cloud adoption roadmaps, project documentation, estimations, and delivery timelines.
• Support implementation teams from concept through delivery, providing architectural guidance and resolving complex technical challenges.
• Stay current with evolving Data Platform and AI architecture patterns and assess how new capabilities can be applied to projects.