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Technologies-expected : Python SQL Apache Spark Microsoft Azure Azure Databricks about-project : Join the team of Experts that transform businesses into data-driven organizations by providing new generation of Business Intelligence solutions including Artificial Intelligence and Machine Learning based on Microsoft Azure and Power Platform responsibilities : Architecture Design: Design and implement scalable, reliable, and secure data platform architectures using Azure services and Azure Databricks. Define end-to-end data processing pipelines, including ingestion, transformation, and consumption layers. Review and optimize current solution based on Medalion Architecture principles Stakeholder Collaboration: Collaborate with Product Owners, Data Engineers, Data Scientists, and Business Stakeholders to align the platform’s architecture with business objectives. Provide technical leadership and guidance to cross-functional teams. Optimization and Scalability: Optimize Databricks workloads and resource management for performance and cost-efficiency. Architect solutions that scale for growing datasets and evolving business needs. Governance and Security: Ensure compliance with data governance and security standards. Implement best practices for managing data privacy, access control, and auditability. Innovation and Best Practices: Stay updated on the latest Azure and Databricks features and identify opportunities to enhance the data platform. Establish architectural standards and reusable frameworks requirements-expected : Technical Expertise: Strong hands-on experience with Azure services, including but not limited to: Azure Databricks Azure Data Factory Azure Synapse Analytics Azure Data Lake (Gen2) Azure Blob Storage Azure Functions Azure Key Vault Proficiency in designing and implementing ETL/ELT pipelines with Databricks notebooks and workflows. Expertise in Spark, SQL, and Python programming within Databricks. Cloud-Native Data Solutions: In-depth understanding of cloud-native data architectures, including serverless computing, distributed systems, and storage optimization in Azure. Data Modeling & Integration: Experience in designing normalized and de-normalized data models. Hands-on experience with integrating various data sources, APIs, and real-time streaming solutions (e.g., Event Hub, Kafka). Performance Tuning and Monitoring: Proficiency in optimizing Databricks clusters and Spark jobs Knowledge of monitoring tools like Azure Monitor, Log Analytics, and Datadog for performance analysis. Security and Compliance: Familiarity with Azure-native security features, such as Key Vault, Managed Identities, and role-based access control (RBAC). Knowledge and understanding of Databricks Unity Catalog Leadership Skills: Ability to lead architectural discussions, resolve conflicts, and drive consensus across technical teams. Mentorship and upskilling of engineering teams on Azure and Databricks best practices. offered : Ability to work remotely Private medical care or Multisport (you choose) Flexible working hours Paid holidays Unlimited access to Microsoft/Snowflake Technology Comfortable and spacious office benefits : sharing the costs of sports activities private medical care sharing the costs of foreign language classes sharing the costs of professional training & courses flexible working time integration events coffee / tea drinks parking space for employees employee referral program charity initiatives