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
