Top Data Engineer Jobs in Hungary

The Data Engineer will design and manage data workflows, develop AI-driven solutions, and maintain Snowflake data pipelines, improving analytics and reporting processes.

The Data Engineer will design and implement features for a regulatory compliance data platform, collaborating with cross-functional teams while ensuring performance and adherence to coding standards.

The Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

Design, build, and operate enterprise reporting and analytics platforms. Create scalable ELT/ETL pipelines, master data foundations, and lakehouse/warehouse semantic models. Deliver Power BI datasets and dashboards, implement data quality, governance, DevOps practices, and cost-management data solutions. Partner with finance and stakeholders and provide technical leadership across architecture, deployment, and run-state support.

This role supports Supply Chain operations by improving data quality, managing data transformation, and designing data models for visualization.

The Data Engineer will design and operate scalable ingestion pipelines on Azure Fabric, develop Python libraries, and implement best engineering practices. The role requires collaboration with data architects and analytics engineers to deliver data products and ensure governance adherence.

The Senior Data Engineer will design and develop scalable data pipelines, manage data lakes, ensure code quality, and mentor team members using modern data technologies.

The AI Systems & Data Engineer will handle data migration, build AI solutions, integrate systems, and automate workflows for HR transformation.

The Senior Cloud Data Engineer designs and implements data solutions on AWS, optimizing data pipelines, writing SQL and Python code, and managing deployments with DevOps practices.

Design and build real-time data pipelines using ClickHouse and Google Cloud. Focus on data quality and optimize financial datasets for analytics.

Build and optimize data pipelines in Snowflake, automate transformations, and collaborate with technical and business teams to meet project requirements.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

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.

The Data Engineer will design, build, and maintain data pipelines, work cross-functionally to define data requirements, and ensure data is secure and governed while supporting AI initiatives.

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.

This role involves data collection for model training, maintaining cloud infrastructure, collaborating with scientists on data quality and cost, and developing an AI dataset roadmap.

Design and maintain data pipelines, collaborate with stakeholders, ensure data quality, deploy infrastructure as code, and optimize reporting solutions.

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.

Responsible for the design and implementation of enterprise data platform capabilities, leading technical decision-making, and improving engineering practices for scalability and security.

Design and develop a big-data processing engine and heavy ETL pipelines (including geo-location analysis) across cloud and on-prem. Build distributed, partitioned pipeline architectures using Spark/PySpark, Scala, Airflow, Kubernetes, and cloud platforms; follow Agile, clean-code, and software design best practices while supporting deployments and client-facing interactions.

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.

Lead design and implementation of data platforms and pipelines for a large online car marketplace. Simplify and modularize tools, address technical debt, propose improvements, and collaborate with senior engineers, product and engineering managers. Work with AWS Glue/Athena, Python/PySpark, SQL, Airflow and streaming frameworks (Kafka/Firehose) on a Canadian time-zone schedule.

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.

Design, validate and oversee mechanical systems for data centers. Create cost-effective mechanical designs and construction documentation, coordinate with internal teams and external vendors, test installations, analyze performance, and visit sites to supervise builds and ensure quality.

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.