Data engineer állások, munkák Budapesten

• kis- és középvállalati ügyfél eredményes akvizíciója, akvizíciós folyamat hatékony szervezése, új ügyfelek felkutatása, tárgyalás és javaslattétel a banki termékek és azok kondícióit illetően
• meglévő kis- és középvállalati ügyfelekkel való proaktív kapcsolattartás

A cégcsoport üzleti folyamatainak és informatikai rendszereinek feltérképezése, felmérése az éttermek, cukrászdák és a catering egységei szintjén...

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

• Development and operation of data pipelines
• Building data layers in OneDataLake (ODL) Central Data Store Consumer (CDSC)
• Balancing business and IT demands to build modern and efficient pipelines in public cloud environments
• Integration of data preparations into managed processes

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• Operation of Power Platform components within the Cloud Data & Analytics Platform
• Monitoring platform usage, performance, and capacity
• Management and maintenance of Power BI gateways and secure data connections to Azure Lakehouse backend
• Oversight of role-based access control and workspace permissions

• Delivery of complex data engineering projects across industries
• Leading small delivery teams
• Management of customer relationships alone or with a Project Manager
• Mentoring more junior engineers
• Evaluating the quality of junior engineers' work
• Contributing to hiring best-in-class data engineers

• Understanding and aligning with business needs
• Identifying related data requirements
• Participating in technical pre-sales activities including effort estimation and proposal creation
• Architecting and planning robust data models and modern data platforms

• Designing, implementing, testing, and optimizing reliable, efficient, and high-quality data pipelines
• Automating the extraction, loading and transformation of data from a wide variety of sources
• Developing solutions for the automated acquisition of data from source systems

• Design, implement, and maintain scalable BI and data processing solutions
• Develop and operate ETL pipelines for customer, booking, and product data
• Integrate data from various file- and REST-based Magenta APIs
• Generate and deliver reports and datasets for multiple downstream consumers

• Design, build, and maintain large-scale distributed data systems
• Develop data processing pipelines using technologies such as Spark and streaming solutions
• Work on systems that evaluate and ensure the quality and integrity of large-scale knowledge graphs

• Design, develop, and optimize scalable data pipelines for processing large-scale structured and unstructured data
• Ensure reliability, performance, and scalability of data systems
• Build solutions to handle real-time streaming data from multiple sources

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

• Gather and translate business requirements into data-driven solutions
• Create and maintain dashboards, reports, and semantic data models
• Ensure data quality, consistency, and usability across reporting solutions

• Design and implement algorithms to process and analyze sensor data from sources like LiDAR, images, and satellite imagery
• Create algorithms to transform sensor data into actionable insights, such as reconstructing 3D models, segmenting spatial data, or detecting environmental features

• Experience in different data science topics
• Independent delivery of data science projects with product-oriented mindset
• Engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

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

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Integration of data ingestion, processing, transformation, and storage

• Design of Azure cloud infrastructure to support Databricks and data platform workloads
• Implementation and management of Azure cloud infrastructure
• Building and maintaining Azure resources including Resource Groups, VNets, Key Vaults, Storage Accounts, and Azure Active Directory integrations