Data engineer állások, munkák programozó, fejlesztő kategóriában

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Design, build, and maintain robust data pipelines that are scalable, efficient, and meet business needs
• Collaborate with cross-functional teams to understand and translate business requirements into data solutions

• Maintaining and evolving data structures
• Building new ETL flows and maintaining/improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• Shape and implement the company’s data science strategy and drive innovation, with a primary focus on Generative AI and Agentic workflows
• Identify opportunities to leverage data for business value and impact
• Take ownership of the full technical stack for development and deployment

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Maintaining and evolving data structures
• Building new ETL flows and maintaining/improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• 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

• AI és adatvezérelt megoldások bevezetésének, működtetésének és fejlesztésének támogatása
• AI/ML use case-ek, PoC-k és projektek szakmai koordinációja az üzleti és IT területekkel együttműködve
• Üzleti igények felmérése, technológiai lehetőségek azonosítása és a megvalósítás koordinálása

• 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

• Delivery of complex data engineering projects across industries
• Leading small delivery teams
• Management of customer relationships alone or with a Project Manager
• Supporting pre-sales process
• Mentoring more junior engineers
• Contributing to hiring best-in-class data talent

• 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

• Delivery on complex data engineering projects across industries
• Leading small delivery teams
• Managing 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

• Design and build backend services and APIs supporting data ingestion, transformation, and delivery
• Own data storage and pipeline architecture including integration with streaming/event infrastructure
• Implement authentication and authorisation in line with cloud identity and access management

• 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

• Contribute to MDM strategy development
• Contribute to IT projects, developments to ensure the satisfaction of stakeholders
• Lead the professional execution of solution design, implementation and unit testing activities
• Participate in ERP related projects as Developer

• 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

• Application development leadership
• Application implementation oversight
• Application monitoring and issue resolution
• Application maintenance management
• Application support provision
• Data validation against official sources
• Request management for data modification

• Design, develop, and maintain high-quality C++ software components and services.
• Build and integrate scalable APIs, database solutions, and data-processing pipelines.
• Collaborate with data scientists and operations research specialists to bring models into production and industrialize their code.

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...