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• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Design and enforcement of data architecture standards including Delta Lake / Lakehouse architecture and data modeling

• Managing day-to-day operations of Databricks data pipelines, including monitoring, troubleshooting, and performance tuning
• Maintaining Delta Lake data layers (bronze / silver / gold), ensuring data availability, consistency, and smooth pipeline execution

• Design, implement, and manage Azure cloud infrastructure to support Databricks and data platform workloads
• Build and maintain Azure resources including Resource Groups, VNets, Key Vaults, Storage Accounts, and Azure Active Directory (AAD) integrations

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• Web alapú vállalatirányítási rendszer fejlesztése Perl nyelven
• Fejlesztés PostgreSQL adatbázis használatával
• Fejlesztés Linux szerveren
• Fejlesztés bármilyen platformon

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

• Design, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP)
• Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality

• Implementing and improving business objects for mobile network infrastructure in backend systems up to the API layer
• Developing and maintaining business objects including data models, backend logic, and APIs
• Collaborating with internal stakeholders considering requirements related to external partners

Design and implement enterprise-scale data pipelines and advanced analytics dashboards including AI-enabled analytics tools such as Microsoft Copilot Agents and Claude...

• Designing data pipelines
• Implementing data pipelines
• Testing data pipelines
• Optimizing data pipelines
• Automating data extraction, loading and transformation
• Developing automated data acquisition solutions
• Ensuring compliance with data security standards
• Analyzing data flows and processes