Top Data Engineer Jobs in Hungary

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

As a Senior Data Engineer, you'll deliver complex projects using Apache Spark/Databricks, manage customer relationships, mentor junior engineers, and contribute to team success.

Design and implement data architectures, lead projects, collaborate with stakeholders, mentor teams, and ensure code quality.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

Support and enhance the OneStream EPM platform: develop business rules, calculations, workflows and data transforms; troubleshoot integrations and data quality; optimize performance; support releases and testing; produce technical documentation; and collaborate with Finance, Data & Analytics teams and implementation partners to build an Enterprise Performance Management Center of Excellence.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

The Staff Software Engineer will design cloud-native architectures, lead AI solutions, mentor engineers, and influence technical direction across teams.

The Senior DBA/Data Platform Engineer will ensure the reliability, performance, and operational quality of SQL Server databases, supporting critical business applications, and collaborating with engineering teams for production stability and disaster recovery.

Design and develop cloud-native backend services in Rust to process terabytes of data daily. Build and operate data-intensive microservices on AWS and Kubernetes, integrate with distributed databases and messaging systems (Kafka/RabbitMQ), and collaborate across teams to deliver observability features.

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

The Senior Data Platform Engineer will optimize data infrastructure, build ELT pipelines, and collaborate with various teams to enhance data governance and insight-driven decision-making.

Maintain and operate the Power Platform frontend (Power BI, Power Apps, Power Automate, SharePoint) integrated with an Azure Lakehouse. Ensure reliable data connections, gateway management, RBAC and security, monitor performance and refreshes, resolve incidents, coach Self-Service BI teams, produce operational dashboards and documentation, and drive continuous improvement and alignment with backend data engineering standards.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.

Design and build scalable real-time and batch data pipelines for programmatic advertising. Ingest, normalize, and transform bid stream, impression, and revenue data; maintain data warehouses; implement data quality monitoring and privacy compliance; support BI teams and develop analytics and models for yield optimization and partner performance.

Lead Data Engineer responsible for designing and building scalable data solutions. Mentor teams, optimize pipelines, and drive best practices in data architecture, governance, and API development.

Lead development of Data and AI features from data architecture to optimization and simulation. Design scalable data architectures, reliable pipelines, and DataOps/DevOps workflows. Partner with analysts, product managers and supply chain specialists to turn complex logistics data into actionable solutions.

The Principal Software Engineer will design and develop scalable applications for energy and water management, optimize performance, and lead systems architecture as part of a senior technical team.

Design, develop, and operate scalable BI data pipelines and reporting solutions integrating customer, booking, and product data from multiple APIs. Deliver datasets to downstream systems (Data Warehouse, Billing, Kibana), ensure data quality and performance, support AWS-based operations, and help shape a new BI engineering team and technical standards.

Own and evolve a GCP-native data platform from ingestion to reporting. Lead architecture, reliability, observability, data quality, cost optimization, and AI-assisted engineering practices while mentoring engineers and collaborating with product and customer teams.

Design, prototype, and productionize specialised LLMs by working with model weights, attention mechanisms, and efficient architectures. Build reusable Python libraries, run experiments and evaluations, and deploy models on GPU-accelerated AWS infrastructure (SageMaker/EC2/S3). Contribute to research-to-production lifecycle, maintain evaluation frameworks, optimize infrastructure for cost and velocity, and collaborate on the team's research agenda while mentoring junior engineers.

Design, develop, and deploy production-grade ML and AI solutions including LLM fine-tuning, RAG architectures, NLP pipelines, time-series forecasting, supplier risk and anomaly detection, scalable data pipelines, and RESTful integrations with enterprise systems.

Design and maintain scalable data pipelines and platforms, lead migration from Snowflake to client service, propose improvements, drive initiatives, and collaborate with senior engineers, product/project managers, and data analysts.

Own and evolve Enode's data platform and pipelines to support the Flex product: build reliable datasets, ensure data quality and monitoring, enable self-serve analytics, and partner with data science on feature pipelines and model readiness. Drive pragmatic platform improvements, documentation, and tooling to scale data reliability and trust across delivery, billing, and reporting.

Lead delivery of end-to-end data and analytics solutions: build dimensional models, develop Power BI dashboards, perform exploratory analysis, design Azure-based data pipelines, capture client requirements, run scenario modelling, test and assure solutions, prepare client communications and lead project teams.