Data engineer állások Budapesten (it programozás, fejlesztés)

• 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

• Design and implement enterprise-scale data pipelines and advanced analytics dashboards
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

• Collaboration with business stakeholders to gather, analyze, and document requirements within the Wholesale domain
• Translation of business needs into user stories and functional specifications
• Driving continuous improvement of Microsoft Dynamics 365 Sales CRM processes and functionalities

• Lead the end-to-end implementation of data pipelines and GenAI applications on Databricks
• Design and maintain CI/CD, model serving, monitoring, and evaluation frameworks for AI production reliability
• Tune complex Spark jobs and LLM inference patterns for maximum efficiency and minimum latency

• Architect scalable inference services, APIs, and backend components for model-driven and LLM-powered product features
• Productionize AI and ML workflows with strong MLOps practices
• Define and implement evaluation frameworks for model quality, system reliability, latency, and cost

Design and build knowledge tracing and longitudinal learner models that support mastery and progression features surfaced to customers...

• Development of highly scalable services realizing AI/ML functionalities
• Implementation of machine learning solutions addressing computer vision and NLP use cases
• Work with Large Language Models (LLMs) and perform prompt engineering tasks

• Design, build, and ship production retrieval systems
• Own vector store selection and operation including scalability, latency, reliability, cost, and multi-tenant design
• Build and operate indexing and refresh pipelines including chunking, embedding generation, backfills, deletes, and versioned indices

• Structured digital description of products and services for large B2B customers
• Collaboration with Solution Design and Portfolio Management based on product prioritization
• Extraction and structuring of product information including product structure, order parameters, dependencies, and order workflows

• Running workshops with business stakeholders to gather and discuss requirements for invoice layout and design
• Documenting and coordinating business requirements clearly
• Aligning with different stakeholders to clarify open questions and priorities

• Development, optimisation, and maintenance of backend services using Java (Spring Boot)
• Contribution to design decisions for new and existing projects
• Deployment and scaling of applications in AWS (ECS, Lambda, S3, DynamoDB, etc.)

• Üzleti igények összegyűjtése és elemzése
• IT rendszerek és szoftverek elemzése
• Fejlesztési igények meghatározása
• Funkcionális és technikai specifikációk készítése
• Üzleti célok és IT megoldások közötti összhang biztosítása
• Szoftverfejlesztési életciklusban való aktív részvétel

• Home office opportunity
• Participation in projects lasting several months
• Understanding clients’ needs and acting as translator between client and developers
• Responsibility for used functionalities at clients and related questions
• Supporting project manager to promote opportunities as change requests

• Ügyfelek üzleti problémáinak részletes felmérése
• Adatgyűjtés, értékelés és elemzés
• Részletes specifikációk készítése
• Projektek tervezésében való részvétel
• Ügyféllel való folyamatos egyeztetés a projekt tervezésétől a megvalósításig
• Funkciók, modellek tervezése, specifikálása és dokumentálása